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26,902 | Methods for Mapping Forest Disturbance and Degradation from Optical
Earth Observation Data: a Review | cs.CV | Purpose of review: This paper presents a review of the current state of the
art in remote sensing based monitoring of forest disturbances and forest
degradation from optical Earth Observation data. Part one comprises an overview
of currently available optical remote sensing sensors, which can be used for
forest disturb... | computer science |
26,903 | Efficient Image Set Classification using Linear Regression based Image
Reconstruction | cs.CV | We propose a novel image set classification technique using linear regression
models. Downsampled gallery image sets are interpreted as subspaces of a high
dimensional space to avoid the computationally expensive training step. We
estimate regression models for each test image using the class specific gallery
subspaces... | computer science |
26,904 | SubCMap: Subject and Condition Specific Effect Maps | cs.CV | Most widely used statistical analysis methods for neuroimaging data identify
condition related structural alterations in the human brain by detecting group
differences. These methods can construct detailed maps showing population-wide
changes due to a given condition of interest using the data of an appropriate
cohort.... | computer science |
26,905 | Deep Learning for Logo Recognition | cs.CV | In this paper we propose a method for logo recognition using deep learning.
Our recognition pipeline is composed of a logo region proposal followed by a
Convolutional Neural Network (CNN) specifically trained for logo
classification, even if they are not precisely localized. Experiments are
carried out on the FlickrLog... | computer science |
26,906 | Midgar: Detection of people through computer vision in the Internet of
Things scenarios to improve the security in Smart Cities, Smart Towns, and
Smart Homes | cs.CV | Could we use Computer Vision in the Internet of Things for using pictures as
sensors? This is the principal hypothesis that we want to resolve. Currently,
in order to create safety areas, cities, or homes, people use IP cameras.
Nevertheless, this system needs people who watch the camera images, watch the
recording aft... | computer science |
26,907 | ChaLearn Looking at People: A Review of Events and Resources | cs.CV | This paper reviews the historic of ChaLearn Looking at People (LAP) events.
We started in 2011 (with the release of the first Kinect device) to run
challenges related to human action/activity and gesture recognition. Since then
we have regularly organized events in a series of competitions covering all
aspects of visua... | computer science |
26,908 | What are the visual features underlying human versus machine vision? | cs.CV | Although Deep Convolutional Networks (DCNs) are approaching the accuracy of
human observers at object recognition, it is unknown whether they leverage
similar visual representations to achieve this performance. To address this, we
introduce Clicktionary, a web-based game for identifying visual features used
by human ob... | computer science |
26,909 | See the Glass Half Full: Reasoning about Liquid Containers, their Volume
and Content | cs.CV | Humans have rich understanding of liquid containers and their contents; for
example, we can effortlessly pour water from a pitcher to a cup. Doing so
requires estimating the volume of the cup, approximating the amount of water in
the pitcher, and predicting the behavior of water when we tilt the pitcher.
Very little at... | computer science |
26,910 | Full-reference image quality assessment-based B-mode ultrasound image
similarity measure | cs.CV | During the last decades, the number of new full-reference image quality
assessment algorithms has been increasing drastically. Yet, despite of the
remarkable progress that has been made, the medical ultrasound image similarity
measurement remains largely unsolved due to a high level of speckle noise
contamination. Pote... | computer science |
26,911 | A Unified RGB-T Saliency Detection Benchmark: Dataset, Baselines,
Analysis and A Novel Approach | cs.CV | Despite significant progress, image saliency detection still remains a
challenging task in complex scenes and environments. Integrating multiple
different but complementary cues, like RGB and Thermal (RGB-T), may be an
effective way for boosting saliency detection performance. The current research
in this direction, ho... | computer science |
26,912 | Revisiting Deep Intrinsic Image Decompositions | cs.CV | While invaluable for many computer vision applications, decomposing a natural
image into intrinsic reflectance and shading layers represents a challenging,
underdetermined inverse problem. As opposed to strict reliance on conventional
optimization or filtering solutions with strong prior assumptions, deep
learning-base... | computer science |
26,913 | CNN-based Segmentation of Medical Imaging Data | cs.CV | Convolutional neural networks have been applied to a wide variety of computer
vision tasks. Recent advances in semantic segmentation have enabled their
application to medical image segmentation. While most CNNs use two-dimensional
kernels, recent CNN-based publications on medical image segmentation featured
three-dimen... | computer science |
26,914 | Guaranteed Parameter Estimation for Discrete Energy Minimization | cs.CV | Structural learning, a method to estimate the parameters for discrete energy
minimization, has been proven to be effective in solving computer vision
problems, especially in 3D scene parsing. As the complexity of the models
increases, structural learning algorithms turn to approximate inference to
retain tractability. ... | computer science |
26,915 | Looking Beyond Appearances: Synthetic Training Data for Deep CNNs in
Re-identification | cs.CV | Re-identification is generally carried out by encoding the appearance of a
subject in terms of outfit, suggesting scenarios where people do not change
their attire. In this paper we overcome this restriction, by proposing a
framework based on a deep convolutional neural network, SOMAnet, that
additionally models other ... | computer science |
26,916 | Light Source Point Cluster Selection Based Atmosphere Light Estimation | cs.CV | Atmosphere light value is a highly critical parameter in defogging algorithms
that are based on an atmosphere scattering model. Any error in atmosphere light
value will produce a direct impact on the accuracy of scattering computation
and thus bring chromatic distortion to restored images. To address this
problem, this... | computer science |
26,917 | Ordered Pooling of Optical Flow Sequences for Action Recognition | cs.CV | Training of Convolutional Neural Networks (CNNs) on long video sequences is
computationally expensive due to the substantial memory requirements and the
massive number of parameters that deep architectures demand. Early fusion of
video frames is thus a standard technique, in which several consecutive frames
are first a... | computer science |
26,918 | Probabilistic Diffeomorphic Registration: Representing Uncertainty | cs.CV | This paper presents a novel mathematical framework for representing
uncertainty in large deformation diffeomorphic image registration. The Bayesian
posterior distribution over the deformations aligning a moving and a fixed
image is approximated via a variational formulation. A stochastic differential
equation (SDE) mod... | computer science |
26,919 | Two-view 3D Reconstruction for Food Volume Estimation | cs.CV | The increasing prevalence of diet-related chronic diseases coupled with the
ineffectiveness of traditional diet management methods have resulted in a need
for novel tools to accurately and automatically assess meals. Recently,
computer vision based systems that use meal images to assess their content have
been proposed... | computer science |
26,920 | A Digital Fuzzy Edge Detector for Color Images | cs.CV | Edge detection is a classic problem in the field of image processing, which
lays foundations for other tasks such as image segmentation. Conventionally,
this operation is performed using gradient operators such as the Roberts or
Sobel operator, which can discover local changes in intensity levels. These
operators, howe... | computer science |
26,921 | Joint Dictionary Learning for Example-based Image Super-resolution | cs.CV | In this paper, we propose a new joint dictionary learning method for
example-based image super-resolution (SR), using sparse representation. The
low-resolution (LR) dictionary is trained from a set of LR sample image
patches. Using the sparse representation coefficients of these LR patches over
the LR dictionary, the h... | computer science |
26,922 | Comprehension-guided referring expressions | cs.CV | We consider generation and comprehension of natural language referring
expression for objects in an image. Unlike generic "image captioning" which
lacks natural standard evaluation criteria, quality of a referring expression
may be measured by the receiver's ability to correctly infer which object is
being described. F... | computer science |
26,923 | Cost-Effective Active Learning for Deep Image Classification | cs.CV | Recent successes in learning-based image classification, however, heavily
rely on the large number of annotated training samples, which may require
considerable human efforts. In this paper, we propose a novel active learning
framework, which is capable of building a competitive classifier with optimal
feature represen... | computer science |
26,924 | Active Self-Paced Learning for Cost-Effective and Progressive Face
Identification | cs.CV | This paper aims to develop a novel cost-effective framework for face
identification, which progressively maintains a batch of classifiers with the
increasing face images of different individuals. By naturally combining two
recently rising techniques: active learning (AL) and self-paced learning (SPL),
our framework is ... | computer science |
26,925 | Real-Time Optical flow-based Video Stabilization for Unmanned Aerial
Vehicles | cs.CV | This paper describes the development of a novel algorithm to tackle the
problem of real-time video stabilization for unmanned aerial vehicles (UAVs).
There are two main components in the algorithm: (1) By designing a suitable
model for the global motion of UAV, the proposed algorithm avoids the necessity
of estimating ... | computer science |
26,926 | Tumour Ellipsification in Ultrasound Images for Treatment Prediction in
Breast Cancer | cs.CV | Recent advances in using quantitative ultrasound (QUS) methods have provided
a promising framework to non-invasively and inexpensively monitor or predict
the effectiveness of therapeutic cancer responses. One of the earliest steps in
using QUS methods is contouring a region of interest (ROI) inside the tumour in
ultras... | computer science |
26,927 | Learning Linear Dynamical Systems with High-Order Tensor Data for
Skeleton based Action Recognition | cs.CV | In recent years, there has been renewed interest in developing methods for
skeleton-based human action recognition. A skeleton sequence can be naturally
represented as a high-order tensor time series. In this paper, we model and
analyze tensor time series with Linear Dynamical System (LDS) which is the most
common for ... | computer science |
26,928 | Density-Wise Two Stage Mammogram Classification using Texture Exploiting
Descriptors | cs.CV | Breast cancer is becoming pervasive with each passing day. Hence, its early
detection is a big step in saving the life of any patient. Mammography is a
common tool in breast cancer diagnosis. The most important step here is
classification of mammogram patches as normal-abnormal and benign-malignant.
Texture of a brea... | computer science |
26,929 | Boosting Dictionary Learning with Error Codes | cs.CV | In conventional sparse representations based dictionary learning algorithms,
initial dictionaries are generally assumed to be proper representatives of the
system at hand. However, this may not be the case, especially in some systems
restricted to random initializations. Therefore, a supposedly optimal
state-update bas... | computer science |
26,930 | Iterative Block Tensor Singular Value Thresholding for Extraction of Low
Rank Component of Image Data | cs.CV | Tensor principal component analysis (TPCA) is a multi-linear extension of
principal component analysis which converts a set of correlated measurements
into several principal components. In this paper, we propose a new robust TPCA
method to extract the princi- pal components of the multi-way data based on
tensor singula... | computer science |
26,931 | Embedding Watermarks into Deep Neural Networks | cs.CV | Deep neural networks have recently achieved significant progress. Sharing
trained models of these deep neural networks is very important in the rapid
progress of researching or developing deep neural network systems. At the same
time, it is necessary to protect the rights of shared trained models. To this
end, we propo... | computer science |
26,932 | Light Source Estimation with Analytical Path-tracing | cs.CV | We present a novel algorithm for light source estimation in scenes
reconstructed with a RGB-D camera based on an analytically-derived formulation
of path-tracing. Our algorithm traces the reconstructed scene with a custom
path-tracer and computes the analytical derivatives of the light transport
equation from principle... | computer science |
26,933 | Bandwidth limited object recognition in high resolution imagery | cs.CV | This paper proposes a novel method to optimize bandwidth usage for object
detection in critical communication scenarios. We develop two operating models
of active information seeking. The first model identifies promising regions in
low resolution imagery and progressively requests higher resolution regions on
which to ... | computer science |
26,934 | Auxiliary Multimodal LSTM for Audio-visual Speech Recognition and
Lipreading | cs.CV | The Aduio-visual Speech Recognition (AVSR) which employs both the video and
audio information to do Automatic Speech Recognition (ASR) is one of the
application of multimodal leaning making ASR system more robust and accuracy.
The traditional models usually treated AVSR as inference or projection but
strict prior limit... | computer science |
26,935 | Automatic Spatial Context-Sensitive Cloud/Cloud-Shadow Detection in
Multi-Source Multi-Spectral Earth Observation Images: AutoCloud+ | cs.CV | The proposed Earth observation (EO) based value adding system (EO VAS),
hereafter identified as AutoCloud+, consists of an innovative EO image
understanding system (EO IUS) design and implementation capable of automatic
spatial context sensitive cloud/cloud shadow detection in multi source multi
spectral (MS) EO imager... | computer science |
26,936 | Systematic study of color spaces and components for the segmentation of
sky/cloud images | cs.CV | Sky/cloud imaging using ground-based Whole Sky Imagers (WSI) is a
cost-effective means to understanding cloud cover and weather patterns. The
accurate segmentation of clouds in these images is a challenging task, as
clouds do not possess any clear structure. Several algorithms using different
color models have been pro... | computer science |
26,937 | Fusing Deep Learned and Hand-Crafted Features of Appearance, Shape, and
Dynamics for Automatic Pain Estimation | cs.CV | Automatic continuous time, continuous value assessment of a patient's pain
from face video is highly sought after by the medical profession. Despite the
recent advances in deep learning that attain impressive results in many
domains, pain estimation risks not being able to benefit from this due to the
difficulty in obt... | computer science |
26,938 | Image Generation and Editing with Variational Info Generative
AdversarialNetworks | cs.CV | Recently there has been an enormous interest in generative models for images
in deep learning. In pursuit of this, Generative Adversarial Networks (GAN) and
Variational Auto-Encoder (VAE) have surfaced as two most prominent and popular
models. While VAEs tend to produce excellent reconstructions but blurry
samples, GAN... | computer science |
26,939 | Convolutional Oriented Boundaries: From Image Segmentation to High-Level
Tasks | cs.CV | We present Convolutional Oriented Boundaries (COB), which produces multiscale
oriented contours and region hierarchies starting from generic image
classification Convolutional Neural Networks (CNNs). COB is computationally
efficient, because it requires a single CNN forward pass for multi-scale
contour detection and it... | computer science |
26,940 | Computing Egomotion with Local Loop Closures for Egocentric Videos | cs.CV | Finding the camera pose is an important step in many egocentric video
applications. It has been widely reported that, state of the art SLAM
algorithms fail on egocentric videos. In this paper, we propose a robust method
for camera pose estimation, designed specifically for egocentric videos. In an
egocentric video, the... | computer science |
26,941 | 3D Reconstruction of Simple Objects from A Single View Silhouette Image | cs.CV | While recent deep neural networks have achieved promising results for 3D
reconstruction from a single-view image, these rely on the availability of RGB
textures in images and extra information as supervision. In this work, we
propose novel stacked hierarchical networks and an end to end training strategy
to tackle a mo... | computer science |
26,942 | Complex Event Recognition from Images with Few Training Examples | cs.CV | We propose to leverage concept-level representations for complex event
recognition in photographs given limited training examples. We introduce a
novel framework to discover event concept attributes from the web and use that
to extract semantic features from images and classify them into social event
categories with fe... | computer science |
26,943 | Compression of Deep Neural Networks for Image Instance Retrieval | cs.CV | Image instance retrieval is the problem of retrieving images from a database
which contain the same object. Convolutional Neural Network (CNN) based
descriptors are becoming the dominant approach for generating {\it global image
descriptors} for the instance retrieval problem. One major drawback of
CNN-based {\it globa... | computer science |
26,944 | Bringing Impressionism to Life with Neural Style Transfer in Come Swim | cs.CV | Neural Style Transfer is a striking, recently-developed technique that uses
neural networks to artistically redraw an image in the style of a source style
image. This paper explores the use of this technique in a production setting,
applying Neural Style Transfer to redraw key scenes in 'Come Swim' in the style
of the ... | computer science |
26,945 | Effective Multi-Query Expansions: Collaborative Deep Networks for Robust
Landmark Retrieval | cs.CV | Given a query photo issued by a user (q-user), the landmark retrieval is to
return a set of photos with their landmarks similar to those of the query,
while the existing studies on the landmark retrieval focus on exploiting
geometries of landmarks for similarity matches between candidate photos and a
query photo. We ob... | computer science |
26,946 | Transfer learning for multi-center classification of chronic obstructive
pulmonary disease | cs.CV | Chronic obstructive pulmonary disease (COPD) is a lung disease which can be
quantified using chest computed tomography (CT) scans. Recent studies have
shown that COPD can be automatically diagnosed using weakly supervised learning
of intensity and texture distributions. However, up till now such classifiers
have only b... | computer science |
26,947 | A Novel Architecture for Computing Approximate Radon Transform | cs.CV | Radon transform is a type of transform which is used in image processing to
transfer the image into intercept-slope coordinate. Its diagonal properties
made it appropriate for some applications which need processes in different
degrees. Radon transform computation needs a lot of arithmetic operations which
makes it a c... | computer science |
26,948 | Temporal scale selection in time-causal scale space | cs.CV | When designing and developing scale selection mechanisms for generating
hypotheses about characteristic scales in signals, it is essential that the
selected scale levels reflect the extent of the underlying structures in the
signal.
This paper presents a theory and in-depth theoretical analysis about the
scale select... | computer science |
26,949 | Accurate Motion Estimation through Random Sample Aggregated Consensus | cs.CV | We reconsider the classic problem of estimating accurately a 2D
transformation from point matches between images containing outliers. RANSAC
discriminates outliers by randomly generating minimalistic sampled hypotheses
and verifying their consensus over the input data. Its response is based on the
single hypothesis tha... | computer science |
26,950 | Pixel Objectness | cs.CV | We propose an end-to-end learning framework for generating foreground object
segmentations. Given a single novel image, our approach produces pixel-level
masks for all "object-like" regions---even for object categories never seen
during training. We formulate the task as a structured prediction problem of
assigning for... | computer science |
26,951 | 3D Face Morphable Models "In-the-Wild" | cs.CV | 3D Morphable Models (3DMMs) are powerful statistical models of 3D facial
shape and texture, and among the state-of-the-art methods for reconstructing
facial shape from single images. With the advent of new 3D sensors, many 3D
facial datasets have been collected containing both neutral as well as
expressive faces. Howev... | computer science |
26,952 | FusionSeg: Learning to combine motion and appearance for fully automatic
segmention of generic objects in videos | cs.CV | We propose an end-to-end learning framework for segmenting generic objects in
videos. Our method learns to combine appearance and motion information to
produce pixel level segmentation masks for all prominent objects in videos. We
formulate this task as a structured prediction problem and design a two-stream
fully conv... | computer science |
26,953 | Block-wise Lensless Compressive Camera | cs.CV | The existing lensless compressive camera
($\text{L}^2\text{C}^2$)~\cite{Huang13ICIP} suffers from low capture rates,
resulting in low resolution images when acquired over a short time. In this
work, we propose a new regime to mitigate these drawbacks. We replace the
global-based compressive sensing used in the existing... | computer science |
26,954 | Moving to VideoKifu: the last steps toward a fully automatic
record-keeping of a Go game | cs.CV | In a previous paper [ arXiv:1508.03269 ] we described the techniques we
successfully employed for automatically reconstructing the whole move sequence
of a Go game by means of a set of pictures. Now we describe how it is possible
to reconstruct the move sequence by means of a video stream (which may be
provided by an u... | computer science |
26,955 | Higher-order Pooling of CNN Features via Kernel Linearization for Action
Recognition | cs.CV | Most successful deep learning algorithms for action recognition extend models
designed for image-based tasks such as object recognition to video. Such
extensions are typically trained for actions on single video frames or very
short clips, and then their predictions from sliding-windows over the video
sequence are pool... | computer science |
26,956 | Synthetic to Real Adaptation with Generative Correlation Alignment
Networks | cs.CV | Synthetic images rendered from 3D CAD models are useful for augmenting
training data for object recognition algorithms. However, the generated images
are non-photorealistic and do not match real image statistics. This leads to a
large domain discrepancy, causing models trained on synthetic data to perform
poorly on rea... | computer science |
26,957 | High Performance Novel Skin Segmentation Algorithm for Images With
Complex Background | cs.CV | Skin Segmentation is widely used in biometric applications such as face
detection, face recognition, face tracking, and hand gesture recognition.
However, several challenges such as nonlinear illumination, equipment effects,
personal interferences, ethnicity variations, etc., are involved in detection
process that resu... | computer science |
26,958 | Fast and Efficient Skin Detection for Facial Detection | cs.CV | In this paper, an efficient skin detection system is proposed. The algorithm
is based on a very fast efficient pre-processing step utilizing the concept of
ternary conversion in order to identify candidate windows and subsequently, a
novel local two-stage diffusion method which has F-score accuracy of 0.5978 on
SDD dat... | computer science |
26,959 | Holistic Interstitial Lung Disease Detection using Deep Convolutional
Neural Networks: Multi-label Learning and Unordered Pooling | cs.CV | Accurately predicting and detecting interstitial lung disease (ILD) patterns
given any computed tomography (CT) slice without any pre-processing
prerequisites, such as manually delineated regions of interest (ROIs), is a
clinically desirable, yet challenging goal. The majority of existing work
relies on manually-provid... | computer science |
26,960 | Dual Recovery Network with Online Compensation for Image
Super-Resolution | cs.CV | The image super-resolution (SR) methods will essentially lead to a loss of
some high-frequency (HF) information when predicting high-resolution (HR)
images from low-resolution (LR) images without using external references. To
address that, we additionally utilize online retrieved data to facilitate image
SR in a unifie... | computer science |
26,961 | Efficient Feature Matching by Progressive Candidate Search | cs.CV | We present a novel feature matching algorithm that systematically utilizes
the geometric properties of features such as position, scale, and orientation,
in addition to the conventional descriptor vectors. In challenging scenes with
the presence of repetitive patterns or with a large viewpoint change, it is
hard to fin... | computer science |
26,962 | Automatic Generation of Typographic Font from a Small Font Subset | cs.CV | This paper addresses the automatic generation of a typographic font from a
subset of characters. Specifically, we use a subset of a typographic font to
extrapolate additional characters. Consequently, we obtain a complete font
containing a number of characters sufficient for daily use. The automated
generation of Japan... | computer science |
26,963 | A Large-scale Dataset and Benchmark for Similar Trademark Retrieval | cs.CV | Trademark retrieval (TR) has become an important yet challenging problem due
to an ever increasing trend in trademark applications and infringement
incidents. There have been many promising attempts for the TR problem, which,
however, fell impracticable since they were evaluated with limited and mostly
trivial datasets... | computer science |
26,964 | Image De-raining Using a Conditional Generative Adversarial Network | cs.CV | Severe weather conditions such as rain and snow adversely affect the visual
quality of images captured under such conditions thus rendering them useless
for further usage and sharing. In addition, such degraded images drastically
affect performance of vision systems. Hence, it is important to solve the
problem of singl... | computer science |
26,965 | Multimodal Fusion via a Series of Transfers for Noise Removal | cs.CV | Near-infrared imaging has been considered as a solution to provide high
quality photographs in dim lighting conditions. This imaging system captures
two types of multimodal images: one is near-infrared gray image (NGI) and the
other is the visible color image (VCI). NGI is noise-free but it is grayscale,
whereas the VC... | computer science |
26,966 | Perception-based energy functions in seam-cutting | cs.CV | Image stitching is challenging in consumer-level photography, due to
alignment difficulties in unconstrained shooting environment. Recent studies
show that seam-cutting approaches can effectively relieve artifacts generated
by local misalignment. Normally, seam-cutting is described in terms of energy
minimization, howe... | computer science |
26,967 | Greedy Compositional Clustering for Unsupervised Learning of
Hierarchical Compositional Models | cs.CV | This paper proposes to integrate a feature pursuit learning process into a
greedy bottom-up learning scheme. The algorithm combines the benefits of
bottom-up and top-down approaches for learning hierarchical models: It allows
to induce the hierarchical structure of objects in an unsupervised manner,
while avoiding a ha... | computer science |
26,968 | Image Compression with SVD : A New Quality Metric Based On Energy Ratio | cs.CV | Digital image compression is a technique that allows to reduce the size of an
image in order to increase the capacity storage devices and to optimize the use
of network bandwidth. The quality of compressed images with the techniques
based on the discrete cosine transform or the wavelet transform is generally
measured w... | computer science |
26,969 | A New Convolutional Network-in-Network Structure and Its Applications in
Skin Detection, Semantic Segmentation, and Artifact Reduction | cs.CV | The inception network has been shown to provide good performance on image
classification problems, but there are not much evidences that it is also
effective for the image restoration or pixel-wise labeling problems. For image
restoration problems, the pooling is generally not used because the decimated
features are no... | computer science |
26,970 | Loss-Sensitive Generative Adversarial Networks on Lipschitz Densities | cs.CV | In this paper, we present the Lipschitz regularization theory and algorithms
for a novel Loss-Sensitive Generative Adversarial Network (LS-GAN).
Specifically, it trains a loss function to distinguish between real and fake
samples by designated margins, while learning a generator alternately to
produce realistic samples... | computer science |
26,971 | Person Re-Identification via Recurrent Feature Aggregation | cs.CV | We address the person re-identification problem by effectively exploiting a
globally discriminative feature representation from a sequence of tracked human
regions/patches. This is in contrast to previous person re-id works, which rely
on either single frame based person to person patch matching, or graph based
sequenc... | computer science |
26,972 | Nonsmooth Analysis and Subgradient Methods for Averaging in Dynamic Time
Warping Spaces | cs.CV | Time series averaging in dynamic time warping (DTW) spaces has been
successfully applied to improve pattern recognition systems. This article
proposes and analyzes subgradient methods for the problem of finding a sample
mean in DTW spaces. The class of subgradient methods generalizes existing
sample mean algorithms suc... | computer science |
26,973 | Segmentation-free Vehicle License Plate Recognition using ConvNet-RNN | cs.CV | While vehicle license plate recognition (VLPR) is usually done with a sliding
window approach, it can have limited performance on datasets with characters
that are of variable width. This can be solved by hand-crafting algorithms to
prescale the characters. While this approach can work fairly well, the
recognizer is on... | computer science |
26,974 | Using Convolutional Neural Networks to Count Palm Trees in Satellite
Images | cs.CV | In this paper we propose a supervised learning system for counting and
localizing palm trees in high-resolution, panchromatic satellite imagery
(40cm/pixel to 1.5m/pixel). A convolutional neural network classifier trained
on a set of palm and no-palm images is applied across a satellite image scene
in a sliding window ... | computer science |
26,975 | Dirty Pixels: Optimizing Image Classification Architectures for Raw
Sensor Data | cs.CV | Real-world sensors suffer from noise, blur, and other imperfections that make
high-level computer vision tasks like scene segmentation, tracking, and scene
understanding difficult. Making high-level computer vision networks robust is
imperative for real-world applications like autonomous driving, robotics, and
surveill... | computer science |
26,976 | Unsupervised Joint Mining of Deep Features and Image Labels for
Large-scale Radiology Image Categorization and Scene Recognition | cs.CV | The recent rapid and tremendous success of deep convolutional neural networks
(CNN) on many challenging computer vision tasks largely derives from the
accessibility of the well-annotated ImageNet and PASCAL VOC datasets.
Nevertheless, unsupervised image categorization (i.e., without the ground-truth
labeling) is much l... | computer science |
26,977 | Residual and Plain Convolutional Neural Networks for 3D Brain MRI
Classification | cs.CV | In the recent years there have been a number of studies that applied deep
learning algorithms to neuroimaging data. Pipelines used in those studies
mostly require multiple processing steps for feature extraction, although
modern advancements in deep learning for image classification can provide a
powerful framework for... | computer science |
26,978 | DSSD : Deconvolutional Single Shot Detector | cs.CV | The main contribution of this paper is an approach for introducing additional
context into state-of-the-art general object detection. To achieve this we
first combine a state-of-the-art classifier (Residual-101[14]) with a fast
detection framework (SSD[18]). We then augment SSD+Residual-101 with
deconvolution layers to... | computer science |
26,979 | Speech Map: A Statistical Multimodal Atlas of 4D Tongue Motion During
Speech from Tagged and Cine MR Images | cs.CV | Quantitative measurement of functional and anatomical traits of 4D tongue
motion in the course of speech or other lingual behaviors remains a major
challenge in scientific research and clinical applications. Here, we introduce
a statistical multimodal atlas of 4D tongue motion using healthy subjects that
enables a comb... | computer science |
26,980 | A graph cut approach to 3D tree delineation, using integrated airborne
LiDAR and hyperspectral imagery | cs.CV | Recognising individual trees within remotely sensed imagery has important
applications in forest ecology and management. Several algorithms for tree
delineation have been suggested, mostly based on locating local maxima or
inverted basins in raster canopy height models (CHMs) derived from Light
Detection And Ranging (L... | computer science |
26,981 | Training Group Orthogonal Neural Networks with Privileged Information | cs.CV | Learning rich and diverse representations is critical for the performance of
deep convolutional neural networks (CNNs). In this paper, we consider how to
use privileged information to promote inherent diversity of a single CNN model
such that the model can learn better representations and offer stronger
generalization ... | computer science |
26,982 | A Projected Gradient Descent Method for CRF Inference allowing
End-To-End Training of Arbitrary Pairwise Potentials | cs.CV | Are we using the right potential functions in the Conditional Random Field
models that are popular in the Vision community? Semantic segmentation and
other pixel-level labelling tasks have made significant progress recently due
to the deep learning paradigm. However, most state-of-the-art structured
prediction methods ... | computer science |
26,983 | Improved Descriptors for Patch Matching and Reconstruction | cs.CV | We propose a convolutional neural network (ConvNet) based approach for
learning local image descriptors which can be used for significantly improved
patch matching and 3D reconstructions. A multi-resolution ConvNet is used for
learning keypoint descriptors. We also propose a new dataset consisting of an
order of magnit... | computer science |
26,984 | Motion Segmentation via Global and Local Sparse Subspace Optimization | cs.CV | In this paper, we propose a new framework for segmenting feature-based moving
objects under affine subspace model. Since the feature trajectories in practice
are high-dimensional and contain a lot of noise, we firstly apply the sparse
PCA to represent the original trajectories with a low-dimensional global
subspace, wh... | computer science |
26,985 | Large Scale Novel Object Discovery in 3D | cs.CV | We present a method for discovering never-seen-before objects in 3D point
clouds obtained from sensors like Microsoft Kinect. We generate supervoxels
directly from the point cloud data and use them with a Siamese network, built
on a recently proposed 3D convolutional neural network architecture. We use
known objects to... | computer science |
26,986 | Learning Multi-level Region Consistency with Dense Multi-label Networks
for Semantic Segmentation | cs.CV | Semantic image segmentation is a fundamental task in image understanding.
Per-pixel semantic labelling of an image benefits greatly from the ability to
consider region consistency both locally and globally. However, many Fully
Convolutional Network based methods do not impose such consistency, which may
give rise to no... | computer science |
26,987 | Towards End-to-End Face Recognition through Alignment Learning | cs.CV | Plenty of effective methods have been proposed for face recognition during
the past decade. Although these methods differ essentially in many aspects, a
common practice of them is to specifically align the facial area based on the
prior knowledge of human face structure before feature extraction. In most
systems, the f... | computer science |
26,988 | Deep Local Video Feature for Action Recognition | cs.CV | We investigate the problem of representing an entire video using CNN features
for human action recognition. Currently, limited by GPU memory, we have not
been able to feed a whole video into CNN/RNNs for end-to-end learning. A common
practice is to use sampled frames as inputs and video labels as supervision.
One major... | computer science |
26,989 | A Multi-view RGB-D Approach for Human Pose Estimation in Operating Rooms | cs.CV | Many approaches have been proposed for human pose estimation in single and
multi-view RGB images. However, some environments, such as the operating room,
are still very challenging for state-of-the-art RGB methods. In this paper, we
propose an approach for multi-view 3D human pose estimation from RGB-D images
and demon... | computer science |
26,990 | Recovering 3D Planar Arrangements from Videos | cs.CV | Acquiring 3D geometry of real world objects has various applications in 3D
digitization, such as navigation and content generation in virtual
environments. Image remains one of the most popular media for such visual tasks
due to its simplicity of acquisition. Traditional image-based 3D reconstruction
approaches heavily... | computer science |
26,991 | Case Study of a highly automated Layout Analysis and OCR of an
incunabulum: 'Der Heiligen Leben' (1488) | cs.CV | This paper provides the first thorough documentation of a high quality
digitization process applied to an early printed book from the incunabulum
period (1450-1500). The entire OCR related workflow including preprocessing,
layout analysis and text recognition is illustrated in detail using the example
of 'Der Heiligen ... | computer science |
26,992 | Super-resolution Using Constrained Deep Texture Synthesis | cs.CV | Hallucinating high frequency image details in single image super-resolution
is a challenging task. Traditional super-resolution methods tend to produce
oversmoothed output images due to the ambiguity in mapping between low and high
resolution patches. We build on recent success in deep learning based texture
synthesis ... | computer science |
26,993 | Unlabeled Samples Generated by GAN Improve the Person Re-identification
Baseline in vitro | cs.CV | The main contribution of this paper is a simple semi-supervised pipeline that
only uses the original training set without collecting extra data. It is
challenging in 1) how to obtain more training data only from the training set
and 2) how to use the newly generated data. In this work, the generative
adversarial networ... | computer science |
26,994 | Pose Invariant Embedding for Deep Person Re-identification | cs.CV | Pedestrian misalignment, which mainly arises from detector errors and pose
variations, is a critical problem for a robust person re-identification (re-ID)
system. With bad alignment, the background noise will significantly compromise
the feature learning and matching process. To address this problem, this paper
introdu... | computer science |
26,995 | Deep Region Hashing for Efficient Large-scale Instance Search from
Images | cs.CV | Instance Search (INS) is a fundamental problem for many applications, while
it is more challenging comparing to traditional image search since the
relevancy is defined at the instance level.
Existing works have demonstrated the success of many complex ensemble systems
that are typically conducted by firstly generatin... | computer science |
26,996 | Quasi-homography warps in image stitching | cs.CV | The naturalness of warps is gaining extensive attentions in image stitching.
Recent warps such as SPHP and AANAP, use global similarity warps to mitigate
projective distortion (which enlarges regions), however, they necessarily bring
in perspective distortion (which generates inconsistencies). In this paper, we
propose... | computer science |
26,997 | UmUTracker: A versatile MATLAB program for automated particle tracking
of 2D light microscopy or 3D digital holography data | cs.CV | We present a versatile and fast MATLAB program (UmUTracker) that
automatically detects and tracks particles by analyzing video sequences
acquired by either light microscopy or digital in-line holographic microscopy.
Our program detects the 2D lateral positions of particles with an algorithm
based on the isosceles trian... | computer science |
26,998 | Camera-trap images segmentation using multi-layer robust principal
component analysis | cs.CV | The segmentation of animals from camera-trap images is a difficult task. To
illustrate, there are various challenges due to environmental conditions and
hardware limitation in these images. We proposed a multi-layer robust principal
component analysis (multi-layer RPCA) approach for background subtraction. Our
method c... | computer science |
26,999 | An Efficient Algebraic Solution to the Perspective-Three-Point Problem | cs.CV | In this work, we present an algebraic solution to the classical
perspective-3-point (P3P) problem for determining the position and attitude of
a camera from observations of three known reference points. In contrast to
previous approaches, we first directly determine the camera's attitude by
employing the corresponding ... | computer science |
27,000 | Detection of Face using Viola Jones and Recognition using Back
Propagation Neural Network | cs.CV | Detection and recognition of the facial images of people is an intricate
problem which has garnered much attention during recent years due to its ever
increasing applications in numerous fields. It continues to pose a challenge in
finding a robust solution to it. Its scope extends to catering the security,
commercial a... | computer science |
27,001 | Exploiting saliency for object segmentation from image level labels | cs.CV | There have been remarkable improvements in the semantic labelling task in the
recent years. However, the state of the art methods rely on large-scale
pixel-level annotations. This paper studies the problem of training a
pixel-wise semantic labeller network from image-level annotations of the
present object classes. Rec... | computer science |
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