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40,210 | Supersaliency: Predicting Smooth Pursuit-Based Attention with Slicing
CNNs Improves Fixation Prediction for Naturalistic Videos | cs.CV | Predicting attention is a popular topic at the intersection of human and
computer vision, but video saliency prediction has only recently begun to
benefit from deep learning-based approaches. Even though most of the available
video-based saliency data sets and models claim to target human observers'
fixations, they fai... | computer science |
40,211 | Deflecting Adversarial Attacks with Pixel Deflection | cs.CV | CNNs are poised to become integral parts of many critical systems. Despite
their robustness to natural variations, image pixel values can be manipulated,
via small, carefully crafted, imperceptible perturbations, to cause a model to
misclassify images. We present an algorithm to process an image so that
classification ... | computer science |
40,212 | Meshed Up: Learnt Error Correction in 3D Reconstructions | cs.CV | Dense reconstructions often contain errors that prior work has so far
minimised using high quality sensors and regularising the output. Nevertheless,
errors still persist. This paper proposes a machine learning technique to
identify errors in three dimensional (3D) meshes. Beyond simply identifying
errors, our method q... | computer science |
40,213 | KRISM --- Krylov Subspace-based Optical Computing of Hyperspectral
Images | eess.IV | Low-rank modeling of hyperspectral images has found extensive use in numerous
inference tasks. In this paper, we present an adaptive imaging technique that
optically computes a low-rank representation of the scene's hyperspectral
image. We make significant contributions towards simultaneously highly
resolvable spectral... | computer science |
40,214 | Road Damage Detection Using Deep Neural Networks with Images Captured
Through a Smartphone | cs.CV | Research on damage detection of road surfaces using image processing
techniques has been actively conducted, achieving considerably high detection
accuracies. Many studies only focus on the detection of the presence or absence
of damage. However, in a real-world scenario, when the road managers from a
governing body ne... | computer science |
40,215 | Hyper-Hue and EMAP on Hyperspectral Images for Supervised Layer
Decomposition of Old Master Drawings | cs.CV | Old master drawings were mostly created step by step in several layers using
different materials. To art historians and restorers, examination of these
layers brings various insights into the artistic work process and helps to
answer questions about the object, its attribution and its authenticity.
However, these layer... | computer science |
40,216 | Malaria Detection Using Image Processing and Machine Learning | eess.IV | Malaria is mosquito-borne blood disease caused by parasites of the genus
Plasmodium. Conventional diagnostic tool for malaria is the examination of
stained blood cell of patient in microscope. The blood to be tested is placed
in a slide and is observed under a microscope to count the number of infected
RBC. An expert t... | computer science |
40,217 | Synchronization Detection and Recovery of Steganographic Messages with
Adversarial Learning | cs.CV | As a means for secret communication, steganography aims at concealing a
message within a medium such that the presence of the hidden message can hardly
be detected. In computer vision tasks, adversarial training has be-come a
competitive learning method to generate images. However, the gen-erative tasks
are confronted ... | computer science |
40,218 | Robust 3D Human Motion Reconstruction Via Dynamic Template Construction | cs.CV | In multi-view human body capture systems, the recovered 3D geometry or even
the acquired imagery data can be heavily corrupted due to occlusions, noise,
limited field of- view, etc. Direct estimation of 3D pose, body shape or motion
on these low-quality data has been traditionally challenging.In this paper, we
present ... | computer science |
40,219 | Weighted Nonlocal Total Variation in Image Processing | cs.CV | In this paper, a novel weighted nonlocal total variation (WNTV) method is
proposed. Compared to the classical nonlocal total variation methods, our
method modifies the energy functional to introduce a weight to balance between
the labeled sets and unlabeled sets. With extensive numerical examples in
semi-supervised clu... | computer science |
40,220 | When can $l_p$-norm objective functions be minimized via graph cuts? | cs.DS | Techniques based on minimal graph cuts have become a standard tool for
solving combinatorial optimization problems arising in image processing and
computer vision applications. These techniques can be used to minimize
objective functions written as the sum of a set of unary and pairwise terms,
provided that the objecti... | computer science |
40,221 | Convolutional neural network-based regression for depth prediction in
digital holography | cs.CV | Digital holography enables us to reconstruct objects in three-dimensional
space from holograms captured by an imaging device. For the reconstruction, we
need to know the depth position of the recoded object in advance. In this
study, we propose depth prediction using convolutional neural network
(CNN)-based regression.... | computer science |
40,222 | Object Detection and Sorting by Using a Global Texture-Shape 3D Feature
Descriptor | cs.CV | Object recognition and sorting plays a key role in robotic systems,
especially for the autonomous robots to implement object sorting tasks in a
warehouse. In this paper, we present a global texture-shape 3D feature
descriptor which can be utilized in a sorting system, and this system can
perform object sorting tasks we... | computer science |
40,223 | Multispectral Compressive Imaging Strategies using Fabry-Pérot
Filtered Sensors | cs.CV | This paper introduces two acquisition device architectures for multispectral
compressive imaging. Unlike most existing methods, the proposed computational
imaging techniques do not include any dispersive element, as they use a
dedicated sensor which integrates narrowband Fabry-P\'erot spectral filters at
the pixel leve... | computer science |
40,224 | Musical Chair: Efficient Real-Time Recognition Using Collaborative IoT
Devices | cs.CV | The prevalence of Internet of things (IoT) devices and abundance of sensor
data has created an increase in real-time data processing such as recognition
of speech, image, and video. While currently such processes are offloaded to
the computationally powerful cloud system, a localized and distributed approach
is desirab... | computer science |
40,225 | Object Detection on Dynamic Occupancy Grid Maps Using Deep Learning and
Automatic Label Generation | cs.CV | We tackle the problem of object detection and pose estimation in a shared
space downtown environment. For perception multiple laser scanners with
360{\deg} coverage were fused in a dynamic occupancy grid map (DOGMa). A
single-stage deep convolutional neural network is trained to provide object
hypotheses comprising of ... | computer science |
40,226 | The Heart of an Image: Quantum Superposition and Entanglement in Visual
Perception | cs.CV | We analyse the way in which the principle that 'the whole is greater than the
sum of its parts' manifests itself with phenomena of visual perception. For
this investigation we use insights and techniques coming from quantum
cognition, and more specifically we are inspired by the correspondence of this
principle with th... | computer science |
40,227 | On the Generalizability of Linear and Non-Linear Region of
Interest-Based Multivariate Regression Models for fMRI Data | stat.AP | In contrast to conventional, univariate analysis, various types of
multivariate analysis have been applied to functional magnetic resonance
imaging (fMRI) data. In this paper, we compare two contemporary approaches for
multivariate regression on task-based fMRI data: linear regression with ridge
regularization and non-... | computer science |
40,228 | MRI Tumor Segmentation with Densely Connected 3D CNN | eess.IV | Glioma is one of the most common and aggressive types of primary brain
tumors. The accurate segmentation of subcortical brain structures is crucial to
the study of gliomas in that it helps the monitoring of the progression of
gliomas and aids the evaluation of treatment outcomes. However, the large
amount of required h... | computer science |
40,229 | Learning to score and summarize figure skating sport videos | cs.MM | This paper focuses on fully understanding the figure skating sport videos. In
particular, we present a large-scale figure skating sport video dataset, which
include 500 figure skating videos. On average, the length of each video is 2
minute and 50 seconds. Each video is annotated by three scores from nine
different ref... | computer science |
40,230 | Augmented Reality needle ablation guidance tool for Irreversible
Electroporation in the pancreas | cs.CV | Irreversible electroporation (IRE) is a soft tissue ablation technique
suitable for treatment of inoperable tumours in the pancreas. The process
involves applying a high voltage electric field to the tissue containing the
mass using needle electrodes, leaving cancerous cells irreversibly damaged and
vulnerable to apopt... | computer science |
40,231 | Gaussian Process Landmarking on Manifolds | stat.ME | As a means of improving analysis of biological shapes, we propose a greedy
algorithm for sampling a Riemannian manifold based on the uncertainty of a
Gaussian process. This is known to produce a near optimal experimental design
with the manifold as the domain, and appears to outperform the use of
user-placed landmarks ... | computer science |
40,232 | Vehicle Pose and Shape Estimation through Multiple Monocular Vision | cs.CV | In this paper, we present an accurate approach to estimate vehicles' pose and
shape from off-board multiview images. The images are taken by monocular
cameras and have small overlaps. We utilize state-of-the-art convolutional
neural networks (CNNs) to extract vehicles' semantic keypoints and introduce a
Cross Projectio... | computer science |
40,233 | Lightweight Classification of IoT Malware based on Image Recognition | cs.CR | The Internet of Things (IoT) is an extension of the traditional Internet,
which allows a very large number of smart devices, such as home appliances,
network cameras, sensors and controllers to connect to one another to share
information and improve user experiences. Current IoT devices are typically
micro-computers fo... | computer science |
40,234 | Deep Learning Models Delineates Multiple Nuclear Phenotypes in H&E
Stained Histology Sections | cs.CV | Nuclear segmentation is an important step for profiling aberrant regions of
histology sections. However, segmentation is a complex problem as a result of
variations in nuclear geometry (e.g., size, shape), nuclear type (e.g.,
epithelial, fibroblast), and nuclear phenotypes (e.g., vesicular, aneuploidy).
The problem is ... | computer science |
40,235 | DARTS: Deceiving Autonomous Cars with Toxic Signs | cs.CR | Sign recognition is an integral part of autonomous cars. Any
misclassification of traffic signs can potentially lead to a multitude of
disastrous consequences, ranging from a life-threatening accident to a
large-scale interruption of transportation services relying on autonomous cars.
In this paper, we propose and exam... | computer science |
40,236 | Robust Fitting in Computer Vision: Easy or Hard? | cs.CV | Robust model fitting plays a vital role in computer vision, and research into
algorithms for robust fitting continues to be active. Arguably the most popular
paradigm for robust fitting in computer vision is consensus maximisation, which
strives to find the model parameters that maximise the number of inliers.
Despite ... | computer science |
40,237 | Ensemble computation approach to the Hough transform | cs.CC | It is demonstrated that the classical Hough transform with shift-elevation
parametrization of digital straight lines has additive complexity of at most
$\mathcal{O}(n^3 / \log n)$ on a $n\times n$ image. The proof is constructive
and uses ensemble computation approach to build summation circuits. The
proposed method ha... | computer science |
40,238 | Connectivity-Driven Parcellation Methods for the Human Cerebral Cortex | cs.CV | In this thesis, we present robust and fully-automated methods for the
subdivision of the entire human cerebral cortex based on connectivity
information. Our contributions are four-fold: First, we propose a clustering
approach to delineate a cortical parcellation that provides a reliable
abstraction of the brain's funct... | computer science |
40,239 | Invertible Autoencoder for domain adaptation | eess.IV | The unsupervised image-to-image translation aims at finding a mapping between
the source ($A$) and target ($B$) image domains, where in many applications
aligned image pairs are not available at training. This is an ill-posed
learning problem since it requires inferring the joint probability distribution
from marginals... | computer science |
40,240 | EV-FlowNet: Self-Supervised Optical Flow Estimation for Event-based
Cameras | cs.CV | Event-based cameras have shown great promise in a variety of situations where
frame based cameras suffer, such as high speed motions and high dynamic range
scenes. However, developing algorithms for event measurements requires a new
class of hand crafted algorithms. Deep learning has shown great success in
providing mo... | computer science |
40,241 | Non-Local Graph-Based Prediction For Reversible Data Hiding In Images | eess.IV | Reversible data hiding (RDH) is desirable in applications where both the
hidden message and the cover medium need to be recovered without loss. Among
many RDH approaches is prediction-error expansion (PEE), containing two steps:
i) prediction of a target pixel value, and ii) embedding according to the value
of predicti... | computer science |
40,242 | Correlation Flow: Robust Optical Flow Using Kernel Cross-Correlators | cs.RO | Robust velocity and position estimation is crucial for autonomous robot
navigation. The optical flow based methods for autonomous navigation have been
receiving increasing attentions in tandem with the development of micro
unmanned aerial vehicles. This paper proposes a kernel cross-correlator (KCC)
based algorithm to ... | computer science |
40,243 | Real-Time Dense Stereo Matching With ELAS on FPGA Accelerated Embedded
Devices | cs.CV | For many applications in low-power real-time robotics, stereo cameras are the
sensors of choice for depth perception as they are typically cheaper and more
versatile than their active counterparts. Their biggest drawback, however, is
that they do not directly sense depth maps; instead, these must be estimated
through d... | computer science |
40,244 | Least Square Error Method Robustness of Computation: What is not usually
considered and taught | cs.GR | There are many practical applications based on the Least Square Error (LSE)
approximation. It is based on a square error minimization 'on a vertical' axis.
The LSE method is simple and easy also for analytical purposes. However, if
data span is large over several magnitudes or non-linear LSE is used, severe
numerical i... | computer science |
40,245 | Multi-Sensor Integration for Indoor 3D Reconstruction | cs.CV | Outdoor maps and navigation information delivered by modern services and
technologies like Google Maps and Garmin navigators have revolutionized the
lifestyle of many people. Motivated by the desire for similar navigation
systems for indoor usage from consumers, advertisers, emergency
rescuers/responders, etc., many in... | computer science |
40,246 | Stereo obstacle detection for unmanned surface vehicles by IMU-assisted
semantic segmentation | cs.RO | A new obstacle detection algorithm for unmanned surface vehicles (USVs) is
presented. A state-of-the-art graphical model for semantic segmentation is
extended to incorporate boat pitch and roll measurements from the on-board
inertial measurement unit (IMU), and a stereo verification algorithm that
consolidates tentativ... | computer science |
40,247 | SPLATNet: Sparse Lattice Networks for Point Cloud Processing | cs.CV | We present a network architecture for processing point clouds that directly
operates on the collection of points represented as a sparse set of samples in
a high-dimensional lattice. Naively applying convolutions on this lattice
scales poorly both in terms of memory and computational cost as the size of the
lattice inc... | computer science |
40,248 | Closed-form solution to cooperative visual-inertial structure from
motion | cs.RO | This paper considers the problem of visual-inertial sensor fusion in the
cooperative case and it provides new theoretical contributions, which regard
its observability and its resolvability in closed form. The case of two agents
is investigated. Each agent is equipped with inertial sensors (accelerometer
and gyroscope)... | computer science |
40,249 | Machine learning based hyperspectral image analysis: A survey | cs.CV | Hyperspectral sensors enable the study of the chemical properties of scene
materials remotely for the purpose of identification, detection, and chemical
composition analysis of objects in the environment. Hence, hyperspectral images
captured from earth observing satellites and aircraft have been increasingly
important ... | computer science |
40,250 | Edge-Based Recognition of Novel Objects for Robotic Grasping | cs.RO | In this paper, we investigate the problem of grasping novel objects in
unstructured environments. To address this problem, consideration of the object
geometry, reachability and force closure analysis are required. We propose a
framework for grasping unknown objects by localizing contact regions on the
contours formed ... | computer science |
40,251 | Adaptive Deep Learning through Visual Domain Localization | cs.CV | A commercial robot, trained by its manufacturer to recognize a predefined
number and type of objects, might be used in many settings, that will in
general differ in their illumination conditions, background, type and degree of
clutter, and so on. Recent computer vision works tackle this generalization
issue through dom... | computer science |
40,252 | Improving Recall of In Situ Sequencing by Self-Learned Features and a
Graphical Model | cs.CV | Image-based sequencing of mRNA makes it possible to see where in a tissue
sample a given gene is active, and thus discern large numbers of different cell
types in parallel. This is crucial for gaining a better understanding of tissue
development and disease such as cancer. Signals are collected over multiple
staining a... | computer science |
40,253 | Bonnet: An Open-Source Training and Deployment Framework for Semantic
Segmentation in Robotics using CNNs | cs.RO | The ability to interpret a scene is an important capability for a robot that
is supposed to interact with its environment. The knowledge of what is in front
of the robot is, for example, key to navigation, manipulation, or planning.
Semantic segmentation labels each pixel of an image with a class label and thus
provide... | computer science |
40,254 | Building Instance Classification Using Street View Images | cs.CV | Land-use classification based on spaceborne or aerial remote sensing images
has been extensively studied over the past decades. Such classification is
usually a patch-wise or pixel-wise labeling over the whole image. But for many
applications, such as urban population density mapping or urban utility
planning, a classi... | computer science |
40,255 | HBST: A Hamming Distance embedding Binary Search Tree for Visual Place
Recognition | cs.RO | Reliable and efficient Visual Place Recognition is a major building block of
modern SLAM systems. Leveraging on our prior work, in this paper we present a
Hamming Distance embedding Binary Search Tree (HBST) approach for binary
Descriptor Matching and Image Retrieval. HBST allows for descriptor Search and
Insertion in ... | computer science |
40,256 | Constructing Category-Specific Models for Monocular Object-SLAM | cs.RO | We present a new paradigm for real-time object-oriented SLAM with a monocular
camera. Contrary to previous approaches, that rely on object-level models, we
construct category-level models from CAD collections which are now widely
available. To alleviate the need for huge amounts of labeled data, we develop a
rendering ... | computer science |
40,257 | Beyond Pixels: Leveraging Geometry and Shape Cues for Online
Multi-Object Tracking | cs.RO | This paper introduces geometry and object shape and pose costs for
multi-object tracking in urban driving scenarios. Using images from a monocular
camera alone, we devise pairwise costs for object tracks, based on several 3D
cues such as object pose, shape, and motion. The proposed costs are agnostic to
the data associ... | computer science |
40,258 | Self Super-Resolution for Magnetic Resonance Images using Deep Networks | eess.IV | High resolution magnetic resonance~(MR) imaging~(MRI) is desirable in many
clinical applications, however, there is a trade-off between resolution, speed
of acquisition, and noise. It is common for MR images to have worse
through-plane resolution~(slice thickness) than in-plane resolution. In these
MRI images, high fre... | computer science |
40,259 | On the Suitability of $L_p$-norms for Creating and Preventing
Adversarial Examples | cs.CR | Much research effort has been devoted to better understanding adversarial
examples, which are specially crafted inputs to machine-learning models that
are perceptually similar to benign inputs, but are classified differently
(i.e., misclassified). Both algorithms that create adversarial examples and
strategies for defe... | computer science |
40,260 | Mono-Camera 3D Multi-Object Tracking Using Deep Learning Detections and
PMBM Filtering | cs.CV | Monocular cameras are one of the most commonly used sensors in the automotive
industry for autonomous vehicles. One major drawback using a monocular camera
is that it only makes observations in the two dimensional image plane and can
not directly measure the distance to objects. In this paper, we aim at filling
this ga... | computer science |
40,261 | Improving OCR Accuracy on Early Printed Books using Deep Convolutional
Networks | cs.CV | This paper proposes a combination of a convolutional and a LSTM network to
improve the accuracy of OCR on early printed books. While the standard model of
line based OCR uses a single LSTM layer, we utilize a CNN- and Pooling-Layer
combination in advance of an LSTM layer. Due to the higher amount of trainable
parameter... | computer science |
40,262 | Deep-6DPose: Recovering 6D Object Pose from a Single RGB Image | cs.CV | Detecting objects and their 6D poses from only RGB images is an important
task for many robotic applications. While deep learning methods have made
significant progress in visual object detection and segmentation, the object
pose estimation task is still challenging. In this paper, we introduce an
end-toend deep learni... | computer science |
40,263 | PDE-constrained optimization in medical image analysis | math.OC | PDE-constrained optimization problems find many applications in medical image
analysis, for example, neuroimaging, cardiovascular imaging, and oncological
imaging. We review related literature and give examples on the formulation,
discretization, and numerical solution of PDE-constrained optimization problems
for medic... | computer science |
40,264 | SalientDSO: Bringing Attention to Direct Sparse Odometry | cs.CV | Although cluttered indoor scenes have a lot of useful high-level semantic
information which can be used for mapping and localization, most Visual
Odometry (VO) algorithms rely on the usage of geometric features such as
points, lines and planes. Lately, driven by this idea, the joint optimization
of semantic labels and ... | computer science |
40,265 | TSSD: Temporal Single-Shot Object Detection Based on Attention-Aware
LSTM | cs.CV | Temporal object detection has attracted significant attention, but most
popular detection methods can not leverage the rich temporal information in
video or robotic vision. Although many different algorithms have been developed
for video detection task, real-time online approaches are frequently deficient.
In this pape... | computer science |
40,266 | Five-point Fundamental Matrix Estimation for Uncalibrated Cameras | cs.CV | We aim at estimating the fundamental matrix in two views from five
correspondences of rotation invariant features obtained by e.g.\ the SIFT
detector. The proposed minimal solver first estimates a homography from three
correspondences assuming that they are co-planar and exploiting their
rotational components. Then the... | computer science |
40,267 | Fast and robust misalignment correction of Fourier ptychographic
microscopy | cs.CV | Fourier ptychographi cmicroscopy(FPM) is a newly developed computational
imaging technique that can provide gigapixel images with both high resolution
(HR) and wide field of view (FOV). However, the positional misalignment of the
LED array induces a degradation of the reconstruction, especially in the
regions away from... | computer science |
40,268 | Yedrouj-Net: An efficient CNN for spatial steganalysis | cs.CV | For about 10 years, detecting the presence of a secret message hidden in an
image was performed with an Ensemble Classifier trained with Rich features. In
recent years, studies such as Xu et al. have indicated that well-designed
convolutional Neural Networks (CNN) can achieve comparable performance to the
two-step mach... | computer science |
40,269 | Genaue modellbasierte Identifikation von gynäkologischen
Katheterpfaden für die MRT-bildgestützte Brachytherapie | cs.CV | German text, english abstract: Mortality in gynecologic cancers, including
cervical, ovarian, vaginal and vulvar cancers, is more than 6% internationally
[1]. In many countries external radiotherapy is supplemented by brachytherapy
with high locally administered doses as standard. The superior ability of
magnetic reson... | computer science |
40,270 | Fast and accurate computation of orthogonal moments for texture analysis | math.NA | In this work we propose a fast and stable algorithm for the computation of
the orthogonal moments of an image. Indeed, the traditional orthogonal moments
formulations are characterized by a high discriminative power, but also by a
large computational complexity, which limits their real-time application. The
recursive a... | computer science |
40,271 | Fusion of multispectral satellite imagery using a cluster of graphics
processing unit | cs.CV | The paper presents a parallel implementation of existing image fusion methods
on a graphical cluster. Parallel implementations of methods based on discrete
wavelet transformation (Haars and Daubechies discrete wavelet transform) are
developed. Experiments were performed on a cluster using GPU and CPU and
performance ga... | computer science |
40,272 | Automated Map Reading: Image Based Localisation in 2-D Maps Using Binary
Semantic Descriptors | cs.CV | We describe a novel approach to image based localisation in urban
environments using semantic matching between images and a 2-D map. It contrasts
with the vast majority of existing approaches which use image to image database
matching. We use highly compact binary descriptors to represent semantic
features at locations... | computer science |
40,273 | Protecting JPEG Images Against Adversarial Attacks | cs.CV | As deep neural networks (DNNs) have been integrated into critical systems,
several methods to attack these systems have been developed. These adversarial
attacks make imperceptible modifications to an image that fool DNN classifiers.
We present an adaptive JPEG encoder which defends against many of these
attacks. Exper... | computer science |
40,274 | Enhancement of land-use change modeling using convolutional neural
networks and convolutional denoising autoencoders | stat.AP | The neighborhood effect is a key driving factor for the land-use change (LUC)
process. This study applies convolutional neural networks (CNN) to capture
neighborhood characteristics from satellite images and to enhance the
performance of LUC modeling. We develop a hybrid CNN model (conv-net) to
predict the LU transitio... | computer science |
40,275 | Classification based Grasp Detection using Spatial Transformer Network | cs.CV | Robotic grasp detection task is still challenging, particularly for novel
objects. With the recent advance of deep learning, there have been several
works on detecting robotic grasp using neural networks. Typically, regression
based grasp detection methods have outperformed classification based detection
methods in com... | computer science |
40,276 | Efficient and Accurate MRI Super-Resolution using a Generative
Adversarial Network and 3D Multi-Level Densely Connected Network | cs.CV | High-resolution (HR) magnetic resonance images (MRI) provide detailed
anatomical information important for clinical application and quantitative
image analysis. However, HR MRI conventionally comes at the cost of longer scan
time, smaller spatial coverage, and lower signal-to-noise ratio (SNR). Recent
studies have show... | computer science |
40,277 | Predicting Out-of-View Feature Points for Model-Based Camera Pose
Estimation | cs.CV | In this work we present a novel framework that uses deep learning to predict
object feature points that are out-of-view in the input image. This system was
developed with the application of model-based tracking in mind, particularly in
the case of autonomous inspection robots, where only partial views of the
object are... | computer science |
40,278 | Affine Differential Invariants for Invariant Feature Point Detection | cs.CV | Image feature points are detected as pixels which locally maximize a detector
function, two commonly used examples of which are the (Euclidean) image
gradient and the Harris-Stephens corner detector. A major limitation of these
feature detectors are that they are only Euclidean-invariant. In this work we
demonstrate th... | computer science |
40,279 | The Earth ain't Flat: Monocular Reconstruction of Vehicles on Steep and
Graded Roads from a Moving Camera | cs.RO | Accurate localization of other traffic participants is a vital task in
autonomous driving systems. State-of-the-art systems employ a combination of
sensing modalities such as RGB cameras and LiDARs for localizing traffic
participants, but most such demonstrations have been confined to plain roads.
We demonstrate, to th... | computer science |
40,280 | Nonlocality-Reinforced Convolutional Neural Networks for Image Denoising | eess.IV | We introduce a paradigm for nonlocal sparsity reinforced deep convolutional
neural network denoising. It is a combination of a local multiscale denoising
by a convolutional neural network (CNN) based denoiser and a nonlocal denoising
based on a nonlocal filter (NLF) exploiting the mutual similarities between
groups of ... | computer science |
40,281 | Conceptualization of Object Compositions Using Persistent Homology | cs.CV | A topological shape analysis is proposed and utilized to learn concepts that
reflect shape commonalities. Our approach is two-fold: i) a spatial topology
analysis of point cloud segment constellations within objects. Therein
constellations are decomposed and described in an hierarchical manner - from
single segments to... | computer science |
40,282 | Fully Convolutional Grasp Detection Network with Oriented Anchor Box | cs.RO | In this paper, we present a real-time approach to predict multiple grasping
poses for a parallel-plate robotic gripper using RGB images. A model with
oriented anchor box mechanism is proposed and a new matching strategy is used
during the training process. An end-to-end fully convolutional neural network
is employed in... | computer science |
40,283 | Methodology to analyze the accuracy of 3D objects reconstructed with
collaborative robot based monocular LSD-SLAM | cs.CV | SLAM systems are mainly applied for robot navigation while research on
feasibility for motion planning with SLAM for tasks like bin-picking, is
scarce. Accurate 3D reconstruction of objects and environments is important for
planning motion and computing optimal gripper pose to grasp objects. In this
work, we propose th... | computer science |
40,284 | ExpandNet: A Deep Convolutional Neural Network for High Dynamic Range
Expansion from Low Dynamic Range Content | cs.CV | High dynamic range (HDR) imaging provides the capability of handling real
world lighting as opposed to the traditional low dynamic range (LDR) which
struggles to accurately represent images with higher dynamic range. However,
most imaging content is still available only in LDR. This paper presents a
method for generati... | computer science |
40,285 | Hybrid Multi-camera Visual Servoing to Moving Target | cs.CV | Visual servoing is a well-known task in robotics. However, there are still
challenges when multiple sources are combined to accurately guide the robot or
occlusions appear. In this paper we present a novel visual servoing approach
using hybrid multi-camera input data to lead a robot arm accurately to
dynamically moving... | computer science |
40,286 | Learning monocular visual odometry with dense 3D mapping from dense 3D
flow | cs.RO | This paper introduces a fully deep learning approach to monocular SLAM, which
can perform simultaneous localization using a neural network for learning
visual odometry (L-VO) and dense 3D mapping. Dense 2D flow and a depth image
are generated from monocular images by sub-networks, which are then used by a
3D flow assoc... | computer science |
40,287 | Fast Cylinder and Plane Extraction from Depth Cameras for Visual
Odometry | cs.CV | This paper presents CAPE, a method to extract planes and cylinder segments
from organized point clouds, which processes 640x480 depth images on a single
CPU core at an average of 300 Hz, by operating on a grid of planar cells.
While, compared to state-of-the-art plane extraction, the latency of CAPE is
more consistent ... | computer science |
40,288 | 3D Human Pose Estimation in RGBD Images for Robotic Task Learning | cs.CV | We propose an approach to estimate 3D human pose in real world units from a
single RGBD image and show that it exceeds performance of monocular 3D pose
estimation approaches from color as well as pose estimation exclusively from
depth. Our approach builds on robust human keypoint detectors for color images
and incorpor... | computer science |
40,289 | Fast and Accurate Semantic Mapping through Geometric-based Incremental
Segmentation | cs.CV | We propose an efficient and scalable method for incrementally building a
dense, semantically annotated 3D map in real-time. The proposed method assigns
class probabilities to each region, not each element (e.g., surfel and voxel),
of the 3D map which is built up through a robust SLAM framework and
incrementally segment... | computer science |
40,290 | Towards Knowledge Discovery from the Vatican Secret Archives. In Codice
Ratio -- Episode 1: Machine Transcription of the Manuscripts | cs.DL | In Codice Ratio is a research project to study tools and techniques for
analyzing the contents of historical documents conserved in the Vatican Secret
Archives (VSA). In this paper, we present our efforts to develop a system to
support the transcription of medieval manuscripts. The goal is to provide
paleographers with... | computer science |
40,291 | Solving Fourier ptychographic imaging problems via neural network
modeling and TensorFlow | cs.CV | Fourier ptychography is a recently developed imaging approach for large
field-of-view and high-resolution microscopy. Here we model the Fourier
ptychographic forward imaging process using a convolution neural network (CNN)
and recover the complex object information in the network training process. In
this approach, the... | computer science |
40,292 | Fire detection in a still image using colour information | eess.IV | Colour analysis is a crucial step in image-based fire detection algorithms.
Many of the proposed fire detection algorithms in a still image are prone to
false alarms caused by objects with a colour similar to fire. To design a
colour-based system with a better false alarm rate, a new
colour-differentiating conversion m... | computer science |
40,293 | Learning to Localize Sound Source in Visual Scenes | cs.CV | Visual events are usually accompanied by sounds in our daily lives. We pose
the question: Can the machine learn the correspondence between visual scene and
the sound, and localize the sound source only by observing sound and visual
scene pairs like human? In this paper, we propose a novel unsupervised
algorithm to addr... | computer science |
40,294 | Learning Local Distortion Visibility From Image Quality Data-sets | cs.MM | Accurate prediction of local distortion visibility thresholds is critical in
many image and video processing applications. Existing methods require an
accurate modeling of the human visual system, and are derived through
pshycophysical experiments with simple, artificial stimuli. These approaches,
however, are difficul... | computer science |
40,295 | Automated non-mass enhancing lesion detection and segmentation in breast
DCE-MRI | eess.IV | Non-mass enhancing lesions (NME) constitute a diagnostic challenge in dynamic
contrast enhanced magnetic resonance imaging (DCE-MRI) of the breast. Computer
Aided Diagnosis (CAD) systems provide physicians with advanced tools for
analysis, assessment and evaluation that have a significant impact on the
diagnostic perfo... | computer science |
40,296 | Omnidirectional CNN for Visual Place Recognition and Navigation | cs.CV | $ $Visual place recognition is challenging, especially when only a few place
exemplars are given. To mitigate the challenge, we consider place recognition
method using omnidirectional cameras and propose a novel Omnidirectional
Convolutional Neural Network (O-CNN) to handle severe camera pose variation.
Given a visual ... | computer science |
40,297 | A state of the art of urban reconstruction: street, street network,
vegetation, urban feature | cs.OH | World population is raising, especially the part of people living in cities.
With increased population and complex roles regarding their inhabitants and
their surroundings, cities concentrate difficulties for design, planning and
analysis. These tasks require a way to reconstruct/model a city. Traditionally,
much atten... | computer science |
40,298 | Image Segmentation and Processing for Efficient Parking Space Analysis | eess.IV | In this paper, we develop a method to detect vacant parking spaces in an
environment with unclear segments and contours with the help of MATLAB image
processing capabilities. Due to the anomalies present in the parking spaces,
such as uneven illumination, distorted slot lines and overlapping of cars. The
present-day co... | computer science |
40,299 | Multi-Frame Quality Enhancement for Compressed Video | cs.CV | The past few years have witnessed great success in applying deep learning to
enhance the quality of compressed image/video. The existing approaches mainly
focus on enhancing the quality of a single frame, ignoring the similarity
between consecutive frames. In this paper, we investigate that heavy quality
fluctuation ex... | computer science |
40,300 | Towards Monocular Digital Elevation Model (DEM) Estimation by
Convolutional Neural Networks - Application on Synthetic Aperture Radar
Images | eess.SP | Synthetic aperture radar (SAR) interferometry (InSAR) is performed using
repeat-pass geometry. InSAR technique is used to estimate the topographic
reconstruction of the earth surface. The main problem of the range-Doppler
focusing technique is the nature of the two-dimensional SAR result, affected by
the layover indete... | computer science |
40,301 | Approximate Query Matching for Image Retrieval | cs.CV | Traditional image recognition involves identifying the key object in a
portrait-type image with a single object focus (ILSVRC, AlexNet, and VGG). More
recent approaches consider dense image recognition - segmenting an image with
appropriate bounding boxes and performing image recognition within these
bounding boxes (Se... | computer science |
40,302 | Feature Distillation: DNN-Oriented JPEG Compression Against Adversarial
Examples | cs.CV | Deep Neural Networks (DNNs) have achieved remarkable performance in a myriad
of realistic applications. However, recent studies show that well-trained DNNs
can be easily misled by adversarial examples (AE) -- the maliciously crafted
inputs by introducing small and imperceptible input perturbations. Existing
mitigation ... | computer science |
40,303 | XNORBIN: A 95 TOp/s/W Hardware Accelerator for Binary Convolutional
Neural Networks | cs.CV | Deploying state-of-the-art CNNs requires power-hungry processors and off-chip
memory. This precludes the implementation of CNNs in low-power embedded
systems. Recent research shows CNNs sustain extreme quantization, binarizing
their weights and intermediate feature maps, thereby saving 8-32\x memory and
collapsing ener... | computer science |
40,304 | Vision-Aided Absolute Trajectory Estimation Using an Unsupervised Deep
Network with Online Error Correction | cs.CV | We present an unsupervised deep neural network approach to the fusion of
RGB-D imagery with inertial measurements for absolute trajectory estimation.
Our network, dubbed the Visual-Inertial-Odometry Learner (VIOLearner), learns
to perform visual-inertial odometry (VIO) without inertial measurement unit
(IMU) intrinsic ... | computer science |
40,305 | Calculating the Midsagittal Plane for Symmetrical Bilateral Shapes:
Applications to Clinical Facial Surgical Planning | cs.CV | It is difficult to estimate the midsagittal plane of human subjects with
craniomaxillofacial (CMF) deformities. We have developed a LAndmark GEometric
Routine (LAGER), which automatically estimates a midsagittal plane for such
subjects. The LAGER algorithm was based on the assumption that the optimal
midsagittal plane ... | computer science |
40,306 | $EVA^2$ : Exploiting Temporal Redundancy in Live Computer Vision | cs.CV | Hardware support for deep convolutional neural networks (CNNs) is critical to
advanced computer vision in mobile and embedded devices. Current designs,
however, accelerate generic CNNs; they do not exploit the unique
characteristics of real-time vision. We propose to use the temporal redundancy
in natural video to avoi... | computer science |
40,307 | Queuing Theory Guided Intelligent Traffic Scheduling through Video
Analysis using Dirichlet Process Mixture Model | cs.CV | Accurate prediction of traffic signal duration for roadway junction is a
challenging problem due to the dynamic nature of traffic flows. Though
supervised learning can be used, parameters may vary across roadway junctions.
In this paper, we present a computer vision guided expert system that can learn
the departure rat... | computer science |
40,308 | MergeNet: A Deep Net Architecture for Small Obstacle Discovery | cs.CV | We present here, a novel network architecture called MergeNet for discovering
small obstacles for on-road scenes in the context of autonomous driving. The
basis of the architecture rests on the central consideration of training with
less amount of data since the physical setup and the annotation process for
small obsta... | computer science |
40,309 | Convolutional Point-set Representation: A Convolutional Bridge Between a
Densely Annotated Image and 3D Face Alignment | cs.CV | We present a robust method for estimating the facial pose and shape
information from a densely annotated facial image. The method relies on
Convolutional Point-set Representation (CPR), a carefully designed matrix
representation to summarize different layers of information encoded in the set
of detected points in the a... | computer science |
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