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26,402 | A Model of Virtual Carrier Immigration in Digital Images for Region
Segmentation | cs.CV | A novel model for image segmentation is proposed, which is inspired by the
carrier immigration mechanism in physical P-N junction. The carrier diffusing
and drifting are simulated in the proposed model, which imitates the physical
self-balancing mechanism in P-N junction. The effect of virtual carrier
immigration in di... | computer science |
26,403 | The Virtual Electromagnetic Interaction between Digital Images for Image
Matching with Shifting Transformation | cs.CV | A novel way of matching two images with shifting transformation is studied.
The approach is based on the presentation of the virtual edge current in
images, and also the study of virtual electromagnetic interaction between two
related images inspired by electromagnetism. The edge current in images is
proposed as a disc... | computer science |
26,404 | Fast Training of Convolutional Neural Networks via Kernel Rescaling | cs.CV | Training deep Convolutional Neural Networks (CNN) is a time consuming task
that may take weeks to complete. In this article we propose a novel,
theoretically founded method for reducing CNN training time without incurring
any loss in accuracy. The basic idea is to begin training with a pre-train
network using lower-res... | computer science |
26,405 | Analyzing the Affect of a Group of People Using Multi-modal Framework | cs.CV | Millions of images on the web enable us to explore images from social events
such as a family party, thus it is of interest to understand and model the
affect exhibited by a group of people in images. But analysis of the affect
expressed by multiple people is challenging due to varied indoor and outdoor
settings, and i... | computer science |
26,406 | Image Based Camera Localization: an Overview | cs.CV | Recently, virtual reality, augmented reality, robotics, self-driving cars et
al attract much attention of industrial community, in which image based camera
localization is a key task. It is urgent to give an overview of image based
camera localization. In this paper, an overview of image based camera
localization is pr... | computer science |
26,407 | Multi-Task Curriculum Transfer Deep Learning of Clothing Attributes | cs.CV | Recognising detailed clothing characteristics (fine-grained attributes) in
unconstrained images of people in-the-wild is a challenging task for computer
vision, especially when there is only limited training data from the wild
whilst most data available for model learning are captured in well-controlled
environments us... | computer science |
26,408 | Light Field Compression with Disparity Guided Sparse Coding based on
Structural Key Views | cs.CV | Recent imaging technologies are rapidly evolving for sampling richer and more
immersive representations of the 3D world. And one of the emerging technologies
are light field (LF) cameras based on micro-lens arrays. To record the
directional information of the light rays, a much larger storage space and
transmission ban... | computer science |
26,409 | Deep disentangled representations for volumetric reconstruction | cs.CV | We introduce a convolutional neural network for inferring a compact
disentangled graphical description of objects from 2D images that can be used
for volumetric reconstruction. The network comprises an encoder and a
twin-tailed decoder. The encoder generates a disentangled graphics code. The
first decoder generates a v... | computer science |
26,410 | Video Depth-From-Defocus | cs.CV | Many compelling video post-processing effects, in particular aesthetic focus
editing and refocusing effects, are feasible if per-frame depth information is
available. Existing computational methods to capture RGB and depth either
purposefully modify the optics (coded aperture, light-field imaging), or employ
active RGB... | computer science |
26,411 | Semi-Coupled Two-Stream Fusion ConvNets for Action Recognition at
Extremely Low Resolutions | cs.CV | Deep convolutional neural networks (ConvNets) have been recently shown to
attain state-of-the-art performance for action recognition on
standard-resolution videos. However, less attention has been paid to
recognition performance at extremely low resolutions (eLR) (e.g., 16 x 12
pixels). Reliable action recognition usin... | computer science |
26,412 | Stroke Sequence-Dependent Deep Convolutional Neural Network for Online
Handwritten Chinese Character Recognition | cs.CV | In this paper, we propose a novel model, named Stroke Sequence-dependent Deep
Convolutional Neural Network (SSDCNN), using the stroke sequence information
and eight-directional features for Online Handwritten Chinese Character
Recognition (OLHCCR). On one hand, SSDCNN can learn the representation of
Online Handwritten ... | computer science |
26,413 | Video Fill in the Blank with Merging LSTMs | cs.CV | Given a video and its incomplete textural description with missing words, the
Video-Fill-in-the-Blank (ViFitB) task is to automatically find the missing
word. The contextual information of the sentences are important to infer the
missing words; the visual cues are even more crucial to get a more accurate
inference. In ... | computer science |
26,414 | Automatic View-Point Selection for Inter-Operative Endoscopic
Surveillance | cs.CV | Esophageal adenocarcinoma arises from Barrett's esophagus, which is the most
serious complication of gastroesophageal reflux disease. Strategies for
screening involve periodic surveillance and tissue biopsies. A major challenge
in such regular examinations is to record and track the disease evolution and
re-localizatio... | computer science |
26,415 | Embedded real-time stereo estimation via Semi-Global Matching on the GPU | cs.CV | Dense, robust and real-time computation of depth information from
stereo-camera systems is a computationally demanding requirement for robotics,
advanced driver assistance systems (ADAS) and autonomous vehicles. Semi-Global
Matching (SGM) is a widely used algorithm that propagates consistency
constraints along several ... | computer science |
26,416 | GPU-accelerated real-time stixel computation | cs.CV | The Stixel World is a medium-level, compact representation of road scenes
that abstracts millions of disparity pixels into hundreds or thousands of
stixels. The goal of this work is to implement and evaluate a complete
multi-stixel estimation pipeline on an embedded, energy-efficient,
GPU-accelerated device. This work ... | computer science |
26,417 | Assessing Threat of Adversarial Examples on Deep Neural Networks | cs.CV | Deep neural networks are facing a potential security threat from adversarial
examples, inputs that look normal but cause an incorrect classification by the
deep neural network. For example, the proposed threat could result in
hand-written digits on a scanned check being incorrectly classified but looking
normal when hu... | computer science |
26,418 | Improved phase-unwrapping method using geometric constraints | cs.CV | Conventional dual-frequency fringe projection algorithm often suffers from
phase unwrapping failure when the frequency ratio between the high frequency
and the low one is too large. Zhang et.al. proposed an enhanced two-frequency
phase-shifting method to use geometric constraints of digital fringe
projection(DFP) to re... | computer science |
26,419 | Recurrent 3D Attentional Networks for End-to-End Active Object
Recognition in Cluttered Scenes | cs.CV | Active vision is inherently attention-driven: The agent selects views of
observation to best approach the vision task while improving its internal
representation of the scene being observed. Inspired by the recent success of
attention-based models in 2D vision tasks based on single RGB images, we
propose to address the... | computer science |
26,420 | Learning and Fusing Multimodal Features from and for Multi-task Facial
Computing | cs.CV | We propose a deep learning-based feature fusion approach for facial computing
including face recognition as well as gender, race and age detection. Instead
of training a single classifier on face images to classify them based on the
features of the person whose face appears in the image, we first train four
different c... | computer science |
26,421 | On Duality Of Multiple Target Tracking and Segmentation | cs.CV | Traditionally, object tracking and segmentation are treated as two separate
problems and solved independently. However, in this paper, we argue that
tracking and segmentation are actually closely related and solving one should
help the other. On one hand, the object track, which is a set of bounding boxes
with one boun... | computer science |
26,422 | Are Accuracy and Robustness Correlated? | cs.CV | Machine learning models are vulnerable to adversarial examples formed by
applying small carefully chosen perturbations to inputs that cause unexpected
classification errors. In this paper, we perform experiments on various
adversarial example generation approaches with multiple deep convolutional
neural networks includ... | computer science |
26,423 | Comparing Face Detection and Recognition Techniques | cs.CV | This paper implements and compares different techniques for face detection
and recognition. One is find where the face is located in the images that is
face detection and second is face recognition that is identifying the person.
We study three techniques in this paper: Face detection using self organizing
map (SOM), F... | computer science |
26,424 | Deep Learning Ensembles for Melanoma Recognition in Dermoscopy Images | cs.CV | Melanoma is the deadliest form of skin cancer. While curable with early
detection, only highly trained specialists are capable of accurately
recognizing the disease. As expertise is in limited supply, automated systems
capable of identifying disease could save lives, reduce unnecessary biopsies,
and reduce costs. Towar... | computer science |
26,425 | Road Curb Extraction from Mobile LiDAR Point Clouds | cs.CV | Automatic extraction of road curbs from uneven, unorganized, noisy and
massive 3D point clouds is a challenging task. Existing methods often project
3D point clouds onto 2D planes to extract curbs. However, the projection causes
loss of 3D information which degrades the performance of the detection. This
paper presents... | computer science |
26,426 | Incremental One-Class Models for Data Classification | cs.CV | In this paper we outline a PhD research plan. This research contributes to
the field of one-class incremental learning and classification in case of
non-stationary environments. The goal of this PhD is to define a new
classification framework able to deal with very small learning dataset at the
beginning of the process... | computer science |
26,427 | Recovering the Missing Link: Predicting Class-Attribute Associations for
Unsupervised Zero-Shot Learning | cs.CV | Collecting training images for all visual categories is not only expensive
but also impractical. Zero-shot learning (ZSL), especially using attributes,
offers a pragmatic solution to this problem. However, at test time most
attribute-based methods require a full description of attribute associations
for each unseen cla... | computer science |
26,428 | Beyond Spatial Auto-Regressive Models: Predicting Housing Prices with
Satellite Imagery | cs.CV | When modeling geo-spatial data, it is critical to capture spatial
correlations for achieving high accuracy. Spatial Auto-Regression (SAR) is a
common tool used to model such data, where the spatial contiguity matrix (W)
encodes the spatial correlations. However, the efficacy of SAR is limited by
two factors. First, it ... | computer science |
26,429 | To Frontalize or Not To Frontalize: A Study of Face Pre-Processing
Techniques and Their Impact on Recognition | cs.CV | Face recognition performance has improved remarkably in the last decade. Much
of this success can be attributed to the development of deep learning
techniques such as convolutional neural networks (CNNs). While CNNs have pushed
the state-of-the-art forward, their training process requires a large amount of
clean and co... | computer science |
26,430 | Location Sensitive Deep Convolutional Neural Networks for Segmentation
of White Matter Hyperintensities | cs.CV | The anatomical location of imaging features is of crucial importance for
accurate diagnosis in many medical tasks. Convolutional neural networks (CNN)
have had huge successes in computer vision, but they lack the natural ability
to incorporate the anatomical location in their decision making process,
hindering success ... | computer science |
26,431 | Real-time Joint Tracking of a Hand Manipulating an Object from RGB-D
Input | cs.CV | Real-time simultaneous tracking of hands manipulating and interacting with
external objects has many potential applications in augmented reality, tangible
computing, and wearable computing. However, due to difficult occlusions, fast
motions, and uniform hand appearance, jointly tracking hand and object pose is
more cha... | computer science |
26,432 | What is the Best Way for Extracting Meaningful Attributes from Pictures? | cs.CV | Automatic attribute discovery methods have gained in popularity to extract
sets of visual attributes from images or videos for various tasks. Despite
their good performance in some classification tasks, it is difficult to
evaluate whether the attributes discovered by these methods are meaningful and
which methods are t... | computer science |
26,433 | Spatio-Temporal Attention Models for Grounded Video Captioning | cs.CV | Automatic video captioning is challenging due to the complex interactions in
dynamic real scenes. A comprehensive system would ultimately localize and track
the objects, actions and interactions present in a video and generate a
description that relies on temporal localization in order to ground the visual
concepts. Ho... | computer science |
26,434 | Deep Learning Prototype Domains for Person Re-Identification | cs.CV | Person re-identification (re-id) is the task of matching multiple occurrences
of the same person from different cameras, poses, lighting conditions, and a
multitude of other factors which alter the visual appearance. Typically, this
is achieved by learning either optimal features or matching metrics which are
adapted t... | computer science |
26,435 | Spatio-temporal Co-Occurrence Characterizations for Human Action
Classification | cs.CV | The human action classification task is a widely researched topic and is
still an open problem. Many state-of-the-arts approaches involve the usage of
bag-of-video-words with spatio-temporal local features to construct
characterizations for human actions. In order to improve beyond this standard
approach, we investigat... | computer science |
26,436 | Structured Sparse Subspace Clustering: A Joint Affinity Learning and
Subspace Clustering Framework | cs.CV | Subspace clustering refers to the problem of segmenting data drawn from a
union of subspaces. State-of-the-art approaches for solving this problem follow
a two-stage approach. In the first step, an affinity matrix is learned from the
data using sparse or low-rank minimization techniques. In the second step, the
segment... | computer science |
26,437 | Rule Extraction Algorithm for Deep Neural Networks: A Review | cs.CV | Despite the highest classification accuracy in wide varieties of application
areas, artificial neural network has one disadvantage. The way this Network
comes to a decision is not easily comprehensible. The lack of explanation
ability reduces the acceptability of neural network in data mining and decision
system. This ... | computer science |
26,438 | Real-time analysis of cataract surgery videos using statistical models | cs.CV | The automatic analysis of the surgical process, from videos recorded during
surgeries, could be very useful to surgeons, both for training and for
acquiring new techniques. The training process could be optimized by
automatically providing some targeted recommendations or warnings, similar to
the expert surgeon's guida... | computer science |
26,439 | M2CAI Workflow Challenge: Convolutional Neural Networks with Time
Smoothing and Hidden Markov Model for Video Frames Classification | cs.CV | Our approach is among the three best to tackle the M2CAI Workflow challenge.
The latter consists in recognizing the operation phase for each frames of
endoscopic videos. In this technical report, we compare several classification
models and temporal smoothing methods. Our submitted solution is a fine tuned
Residual Net... | computer science |
26,440 | Master's Thesis : Deep Learning for Visual Recognition | cs.CV | The goal of our research is to develop methods advancing automatic visual
recognition. In order to predict the unique or multiple labels associated to an
image, we study different kind of Deep Neural Networks architectures and
methods for supervised features learning. We first draw up a state-of-the-art
review of the C... | computer science |
26,441 | Deep Identity-aware Transfer of Facial Attributes | cs.CV | This paper presents a Deep convolutional network model for Identity-Aware
Transfer (DIAT) of facial attributes. Given the source input image and the
reference attribute, DIAT aims to generate a facial image (i.e., target image)
that not only owns the reference attribute but also keep the same or similar
identity to the... | computer science |
26,442 | From Traditional to Modern : Domain Adaptation for Action Classification
in Short Social Video Clips | cs.CV | Short internet video clips like vines present a significantly wild
distribution compared to traditional video datasets. In this paper, we focus on
the problem of unsupervised action classification in wild vines using
traditional labeled datasets. To this end, we use a data augmentation based
simple domain adaptation st... | computer science |
26,443 | Semantic Decomposition and Recognition of Long and Complex Manipulation
Action Sequences | cs.CV | Understanding continuous human actions is a non-trivial but important problem
in computer vision. Although there exists a large corpus of work in the
recognition of action sequences, most approaches suffer from problems relating
to vast variations in motions, action combinations, and scene contexts. In this
paper, we i... | computer science |
26,444 | Lensless Imaging with Compressive Ultrafast Sensing | cs.CV | Lensless imaging is an important and challenging problem. One notable
solution to lensless imaging is a single pixel camera which benefits from ideas
central to compressive sampling. However, traditional single pixel cameras
require many illumination patterns which result in a long acquisition process.
Here we present ... | computer science |
26,445 | Mixed context networks for semantic segmentation | cs.CV | Semantic segmentation is challenging as it requires both object-level
information and pixel-level accuracy. Recently, FCN-based systems gained great
improvement in this area. Unlike classification networks, combining features of
different layers plays an important role in these dense prediction models, as
these feature... | computer science |
26,446 | StuffNet: Using 'Stuff' to Improve Object Detection | cs.CV | We propose a Convolutional Neural Network (CNN) based algorithm - StuffNet -
for object detection. In addition to the standard convolutional features
trained for region proposal and object detection [31], StuffNet uses
convolutional features trained for segmentation of objects and 'stuff'
(amorphous categories such as ... | computer science |
26,447 | A Robust 3D-2D Interactive Tool for Scene Segmentation and Annotation | cs.CV | Recent advances of 3D acquisition devices have enabled large-scale
acquisition of 3D scene data. Such data, if completely and well annotated, can
serve as useful ingredients for a wide spectrum of computer vision and graphics
works such as data-driven modeling and scene understanding, object detection
and recognition. ... | computer science |
26,448 | An automatic bad band preremoval algorithm for hyperspectral imagery | cs.CV | For most hyperspectral remote sensing applications, removing bad bands, such
as water absorption bands, is a required preprocessing step. Currently, the
commonly applied method is by visual inspection, which is very time-consuming
and it is easy to overlook some noisy bands. In this study, we find an inherent
connectio... | computer science |
26,449 | Learning Robust Video Synchronization without Annotations | cs.CV | Aligning video sequences is a fundamental yet still unsolved component for a
broad range of applications in computer graphics and vision. Most classical
image processing methods cannot be directly applied to related video problems
due to the high amount of underlying data and their limit to small changes in
appearance.... | computer science |
26,450 | POI: Multiple Object Tracking with High Performance Detection and
Appearance Feature | cs.CV | Detection and learning based appearance feature play the central role in data
association based multiple object tracking (MOT), but most recent MOT works
usually ignore them and only focus on the hand-crafted feature and association
algorithms. In this paper, we explore the high-performance detection and deep
learning ... | computer science |
26,451 | A Reinforcement Learning Approach to the View Planning Problem | cs.CV | We present a Reinforcement Learning (RL) solution to the view planning
problem (VPP), which generates a sequence of view points that are capable of
sensing all accessible area of a given object represented as a 3D model. In
doing so, the goal is to minimize the number of view points, making the VPP a
class of set cover... | computer science |
26,452 | Adaptive Substring Extraction and Modified Local NBNN Scoring for Binary
Feature-based Local Mobile Visual Search without False Positives | cs.CV | In this paper, we propose a stand-alone mobile visual search system based on
binary features and the bag-of-visual words framework. The contribution of this
study is three-fold: (1) We propose an adaptive substring extraction method
that adaptively extracts informative bits from the original binary vector and
stores th... | computer science |
26,453 | Retrieving challenging vessel connections in retinal images by line
co-occurrence statistics | cs.CV | Natural images contain often curvilinear structures, which might be
disconnected, or partly occluded. Recovering the missing connection of
disconnected structures is an open issue and needs appropriate geometric
reasoning. We propose to find line co-occurrence statistics from the
centerlines of blood vessels in retinal... | computer science |
26,454 | An Image Dataset of Text Patches in Everyday Scenes | cs.CV | This paper describes a dataset containing small images of text from everyday
scenes. The purpose of the dataset is to support the development of new
automated systems that can detect and analyze text. Although much research has
been devoted to text detection and recognition in scanned documents, relatively
little atten... | computer science |
26,455 | Short-term prediction of localized cloud motion using ground-based sky
imagers | cs.CV | Fine-scale short-term cloud motion prediction is needed for several
applications, including solar energy generation and satellite communications.
In tropical regions such as Singapore, clouds are mostly formed by convection;
they are very localized, and evolve quickly. We capture hemispherical images of
the sky at regu... | computer science |
26,456 | Scalable Pooled Time Series of Big Video Data from the Deep Web | cs.CV | We contribute a scalable implementation of Ryoo et al's Pooled Time Series
algorithm from CVPR 2015. The updated algorithm has been evaluated on a large
and diverse dataset of approximately 6800 videos collected from a crawl of the
deep web related to human trafficking on DARPA's MEMEX effort. We describe the
propertie... | computer science |
26,457 | Multi-view metric learning for multi-instance image classification | cs.CV | It is critical and meaningful to make image classification since it can help
human in image retrieval and recognition, object detection, etc. In this paper,
three-sides efforts are made to accomplish the task. First, visual features
with bag-of-words representation, not single vector, are extracted to
characterize the ... | computer science |
26,458 | Model-based Outdoor Performance Capture | cs.CV | We propose a new model-based method to accurately reconstruct human
performances captured outdoors in a multi-camera setup. Starting from a
template of the actor model, we introduce a new unified implicit representation
for both, articulated skeleton tracking and nonrigid surface shape refinement.
Our method fits the t... | computer science |
26,459 | Fine-grained Recognition in the Noisy Wild: Sensitivity Analysis of
Convolutional Neural Networks Approaches | cs.CV | In this paper, we study the sensitivity of CNN outputs with respect to image
transformations and noise in the area of fine-grained recognition. In
particular, we answer the following questions (1) how sensitive are CNNs with
respect to image transformations encountered during wild image capture?; (2)
how can we predict... | computer science |
26,460 | Deep Models for Engagement Assessment With Scarce Label Information | cs.CV | Task engagement is defined as loadings on energetic arousal (affect), task
motivation, and concentration (cognition). It is usually challenging and
expensive to label cognitive state data, and traditional computational models
trained with limited label information for engagement assessment do not perform
well because o... | computer science |
26,461 | Exploitation of Semantic Keywords for Malicious Event Classification | cs.CV | Learning an event classifier is challenging when the scenes are semantically
different but visually similar. However, as humans, we typically handle such
tasks painlessly by adding our background semantic knowledge. Motivated by this
observation, we aim to provide an empirical study about how additional
information suc... | computer science |
26,462 | Review of Action Recognition and Detection Methods | cs.CV | In computer vision, action recognition refers to the act of classifying an
action that is present in a given video and action detection involves locating
actions of interest in space and/or time. Videos, which contain photometric
information (e.g. RGB, intensity values) in a lattice structure, contain
information that ... | computer science |
26,463 | Enhanced Object Detection via Fusion With Prior Beliefs from Image
Classification | cs.CV | In this paper, we introduce a novel fusion method that can enhance object
detection performance by fusing decisions from two different types of computer
vision tasks: object detection and image classification. In the proposed work,
the class label of an image obtained from image classification is viewed as
prior knowle... | computer science |
26,464 | Automatic Image De-fencing System | cs.CV | Tourists and Wild-life photographers are often hindered in capturing their
cherished images or videos by a fence that limits accessibility to the scene of
interest. The situation has been exacerbated by growing concerns of security at
public places and a need exists to provide a tool that can be used for
post-processin... | computer science |
26,465 | Spectral Angle Based Unary Energy Functions for Spatial-Spectral
Hyperspectral Classification using Markov Random Fields | cs.CV | In this paper, we propose and compare two spectral angle based approaches for
spatial-spectral classification. Our methods use the spectral angle to generate
unary energies in a grid-structured Markov random field defined over the pixel
labels of a hyperspectral image. The first approach is to use the exponential
spect... | computer science |
26,466 | Multitask Learning of Vegetation Biochemistry from Hyperspectral Data | cs.CV | Statistical models have been successful in accurately estimating the
biochemical contents of vegetation from the reflectance spectra. However, their
performance deteriorates when there is a scarcity of sizable amount of ground
truth data for modeling the complex non-linear relationship occurring between
the spectrum an... | computer science |
26,467 | Optimization on Submanifolds of Convolution Kernels in CNNs | cs.CV | Kernel normalization methods have been employed to improve robustness of
optimization methods to reparametrization of convolution kernels, covariate
shift, and to accelerate training of Convolutional Neural Networks (CNNs).
However, our understanding of theoretical properties of these methods has
lagged behind their su... | computer science |
26,468 | Deep image mining for diabetic retinopathy screening | cs.CV | Deep learning is quickly becoming the leading methodology for medical image
analysis. Given a large medical archive, where each image is associated with a
diagnosis, efficient pathology detectors or classifiers can be trained with
virtually no expert knowledge about the target pathologies. However, deep
learning algori... | computer science |
26,469 | On Unifying Multi-View Self-Representations for Clustering by Tensor
Multi-Rank Minimization | cs.CV | In this paper, we address the multi-view subspace clustering problem. Our
method utilizes the circulant algebra for tensor, which is constructed by
stacking the subspace representation matrices of different views and then
rotating, to capture the low rank tensor subspace so that the refinement of the
view-specific subs... | computer science |
26,470 | Real-time Halfway Domain Reconstruction of Motion and Geometry | cs.CV | We present a novel approach for real-time joint reconstruction of 3D scene
motion and geometry from binocular stereo videos. Our approach is based on a
novel variational halfway-domain scene flow formulation, which allows us to
obtain highly accurate spatiotemporal reconstructions of shape and motion. We
solve the unde... | computer science |
26,471 | 3D Hand Pose Tracking and Estimation Using Stereo Matching | cs.CV | 3D hand pose tracking/estimation will be very important in the next
generation of human-computer interaction. Most of the currently available
algorithms rely on low-cost active depth sensors. However, these sensors can be
easily interfered by other active sources and require relatively high power
consumption. As a resu... | computer science |
26,472 | SPiKeS: Superpixel-Keypoints Structure for Robust Visual Tracking | cs.CV | In visual tracking, part-based trackers are attractive since they are robust
against occlusion and deformation. However, a part represented by a rectangular
patch does not account for the shape of the target, while a superpixel does
thanks to its boundary evidence. Nevertheless, tracking superpixels is
difficult due to... | computer science |
26,473 | A coarse-to-fine algorithm for registration in 3D street-view
cross-source point clouds | cs.CV | With the development of numerous 3D sensing technologies, object registration
on cross-source point cloud has aroused researchers' interests. When the point
clouds are captured from different kinds of sensors, there are large and
different kinds of variations. In this study, we address an even more
challenging case in ... | computer science |
26,474 | MultiCol-SLAM - A Modular Real-Time Multi-Camera SLAM System | cs.CV | The basis for most vision based applications like robotics, self-driving cars
and potentially augmented and virtual reality is a robust, continuous
estimation of the position and orientation of a camera system w.r.t the
observed environment (scene). In recent years many vision based systems that
perform simultaneous lo... | computer science |
26,475 | Theoretical Analysis of Active Contours on Graphs | cs.CV | Active contour models based on partial differential equations have proved
successful in image segmentation, yet the study of their geometric formulation
on arbitrary geometric graphs is still at an early stage. In this paper, we
introduce geometric approximations of gradient and curvature, which are used in
the geodesi... | computer science |
26,476 | Record Counting in Historical Handwritten Documents with Convolutional
Neural Networks | cs.CV | In this paper, we investigate the use of Convolutional Neural Networks for
counting the number of records in historical handwritten documents. With this
work we demonstrate that training the networks only with synthetic images
allows us to perform a near perfect evaluation of the number of records printed
on historical... | computer science |
26,477 | Deep Multi-scale Location-aware 3D Convolutional Neural Networks for
Automated Detection of Lacunes of Presumed Vascular Origin | cs.CV | Lacunes of presumed vascular origin (lacunes) are associated with an
increased risk of stroke, gait impairment, and dementia and are a primary
imaging feature of the small vessel disease. Quantification of lacunes may be
of great importance to elucidate the mechanisms behind neuro-degenerative
disorders and is recommen... | computer science |
26,478 | Feature Sensitive Label Fusion with Random Walker for Atlas-based Image
Segmentation | cs.CV | In this paper, a novel label fusion method is proposed for brain magnetic
resonance image segmentation. This label fusion method is formulated on a
graph, which embraces both label priors from atlases and anatomical priors from
target image. To represent a pixel in a comprehensive way, three kinds of
feature vectors ar... | computer science |
26,479 | Laplacian regularized low rank subspace clustering | cs.CV | The problem of fitting a union of subspaces to a collection of data points
drawn from multiple subspaces is considered in this paper. In the traditional
low rank representation model, the dictionary used to represent the data points
is chosen as the data points themselves and thus the dictionary is corrupted
with noise... | computer science |
26,480 | Automated OCT Segmentation for Images with DME | cs.CV | This paper presents a novel automated system that segments six sub-retinal
layers from optical coherence tomography (OCT) image stacks of healthy patients
and patients with diabetic macular edema (DME). First, each image in the OCT
stack is denoised using a Wiener deconvolution algorithm that estimates the
additive spe... | computer science |
26,481 | A data augmentation methodology for training machine/deep learning gait
recognition algorithms | cs.CV | There are several confounding factors that can reduce the accuracy of gait
recognition systems. These factors can reduce the distinctiveness, or alter the
features used to characterise gait, they include variations in clothing,
lighting, pose and environment, such as the walking surface. Full invariance to
all confound... | computer science |
26,482 | Camera Fingerprint: A New Perspective for Identifying User's Identity | cs.CV | Identifying user's identity is a key problem in many data mining
applications, such as product recommendation, customized content delivery and
criminal identification. Given a set of accounts from the same or different
social network platforms, user identification attempts to identify all accounts
belonging to the same... | computer science |
26,483 | mdBrief - A Fast Online Adaptable, Distorted Binary Descriptor for
Real-Time Applications Using Calibrated Wide-Angle Or Fisheye Cameras | cs.CV | Fast binary descriptors build the core for many vision based applications
with real-time demands like object detection, Visual Odometry or SLAM. Commonly
it is assumed, that the acquired images and thus the patches extracted around
keypoints originate from a perspective projection ignoring image distortion or
completel... | computer science |
26,484 | Maxmin convolutional neural networks for image classification | cs.CV | Convolutional neural networks (CNN) are widely used in computer vision,
especially in image classification. However, the way in which information and
invariance properties are encoded through in deep CNN architectures is still an
open question. In this paper, we propose to modify the standard convo- lutional
block of C... | computer science |
26,485 | Anatomically Constrained Video-CT Registration via the V-IMLOP Algorithm | cs.CV | Functional endoscopic sinus surgery (FESS) is a surgical procedure used to
treat acute cases of sinusitis and other sinus diseases. FESS is fast becoming
the preferred choice of treatment due to its minimally invasive nature.
However, due to the limited field of view of the endoscope, surgeons rely on
navigation system... | computer science |
26,486 | PATH: Person Authentication using Trace Histories | cs.CV | In this paper, a solution to the problem of Active Authentication using trace
histories is addressed. Specifically, the task is to perform user verification
on mobile devices using historical location traces of the user as a function of
time. Considering the movement of a human as a Markovian motion, a modified
Hidden ... | computer science |
26,487 | End-to-end Learning of Deep Visual Representations for Image Retrieval | cs.CV | While deep learning has become a key ingredient in the top performing methods
for many computer vision tasks, it has failed so far to bring similar
improvements to instance-level image retrieval. In this article, we argue that
reasons for the underwhelming results of deep methods on image retrieval are
threefold: i) no... | computer science |
26,488 | Spatial Relationship Based Features for Indian Sign Language Recognition | cs.CV | In this paper, the task of recognizing signs made by hearing impaired people
at sentence level has been addressed. A novel method of extracting spatial
features to capture hand movements of a signer has been proposed. Frames of a
given video of a sign are preprocessed to extract face and hand components of a
signer. Th... | computer science |
26,489 | Predicting First Impressions with Deep Learning | cs.CV | Describable visual facial attributes are now commonplace in human biometrics
and affective computing, with existing algorithms even reaching a sufficient
point of maturity for placement into commercial products. These algorithms
model objective facets of facial appearance, such as hair and eye color,
expression, and as... | computer science |
26,490 | Incremental Nonparametric Weighted Feature Extraction for OnlineSubspace
Pattern Classification | cs.CV | In this paper, a new online method based on nonparametric weighted feature
extraction (NWFE) is proposed. NWFE was introduced to enjoy optimum
characteristics of linear discriminant analysis (LDA) and nonparametric
discriminant analysis (NDA) while rectifying their drawbacks. It emphasizes the
points near decision boun... | computer science |
26,491 | Video Analysis of "YouTube Funnies" to Aid the Study of Human Gait and
Falls - Preliminary Results and Proof of Concept | cs.CV | Because falls are funny, YouTube and other video sharing sites contain a
large repository of real-life falls. We propose extracting gait and balance
information from these videos to help us better understand some of the factors
that contribute to falls. Proof-of-concept is explored in a single video
containing multiple... | computer science |
26,492 | Estimating the concentration of gold nanoparticles incorporated on
Natural Rubber membranes using Multi-Level Starlet Optimal Segmentation | cs.CV | This study consolidates Multi-Level Starlet Segmentation (MLSS) and
Multi-Level Starlet Optimal Segmentation (MLSOS), techniques for
photomicrograph segmentation that use starlet wavelet detail levels to separate
areas of interest in an input image. Several segmentation levels can be
obtained using Multi-Level Starlet ... | computer science |
26,493 | Mask-off: Synthesizing Face Images in the Presence of Head-mounted
Displays | cs.CV | A head-mounted display (HMD) could be an important component of augmented
reality system. However, as the upper face region is seriously occluded by the
device, the user experience could be affected in applications such as
telecommunication and multi-player video games. In this paper, we first present
a novel experimen... | computer science |
26,494 | Iterative Inversion of Deformation Vector Fields with Feedback Control | cs.CV | Purpose: This study aims at improving both accuracy with respect to inverse
consistency and efficiency for numerical DVF inversion, by the development of a
fixed-point iteration method with feedback control. Method: We introduce an
iterative method with active feedback control for DVF inversion, its analysis
and adapta... | computer science |
26,495 | Joint Detection and Tracking for Multipath Targets: A Variational
Bayesian Approach | cs.CV | Different from traditional point target tracking systems assuming that a
target generates at most one single measurement per scan, there exists a class
of multipath target tracking systems where each measurement may originate from
the interested target via one of multiple propagation paths or from clutter,
while the co... | computer science |
26,496 | Exploiting Structure Sparsity for Covariance-based Visual Representation | cs.CV | The past few years have witnessed increasing research interest on
covariance-based feature representation. A variety of methods have been
proposed to boost its efficacy, with some recent ones resorting to nonlinear
kernel technique. Noting that the essence of this feature representation is to
characterise the underlyin... | computer science |
26,497 | Automated Management of Pothole related Disasters Using Image Processing
and Geotagging | cs.CV | Potholes though seem inconsequential, may cause accidents resulting in loss
of human life. In this paper, we present an automated system to efficiently
manage the potholes in a ward by deploying geotagging and image processing
techniques that overcomes the drawbacks associated with the existing
survey-oriented systems.... | computer science |
26,498 | Single- and Multi-Task Architectures for Surgical Workflow Challenge at
M2CAI 2016 | cs.CV | The surgical workflow challenge at M2CAI 2016 consists of identifying 8
surgical phases in cholecystectomy procedures. Here, we propose to use deep
architectures that are based on our previous work where we presented several
architectures to perform multiple recognition tasks on laparoscopic videos. In
this technical r... | computer science |
26,499 | Single- and Multi-Task Architectures for Tool Presence Detection
Challenge at M2CAI 2016 | cs.CV | The tool presence detection challenge at M2CAI 2016 consists of identifying
the presence/absence of seven surgical tools in the images of cholecystectomy
videos. Here, we propose to use deep architectures that are based on our
previous work where we presented several architectures to perform multiple
recognition tasks ... | computer science |
26,500 | Tool and Phase recognition using contextual CNN features | cs.CV | A transfer learning method for generating features suitable for surgical
tools and phase recognition from the ImageNet classification features [1] is
proposed here. In addition, methods are developed for generating contextual
features and combining them with time series analysis for final classification
using multi-cla... | computer science |
26,501 | Detecting People in Artwork with CNNs | cs.CV | CNNs have massively improved performance in object detection in photographs.
However research into object detection in artwork remains limited. We show
state-of-the-art performance on a challenging dataset, People-Art, which
contains people from photos, cartoons and 41 different artwork movements. We
achieve this high ... | computer science |
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