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25,302 | Learning Robust Deep Face Representation | cs.CV | With the development of convolution neural network, more and more researchers
focus their attention on the advantage of CNN for face recognition task. In
this paper, we propose a deep convolution network for learning a robust face
representation. The deep convolution net is constructed by 4 convolution
layers, 4 max po... | computer science |
25,303 | Classification of Complex Wishart Matrices with a Diffusion-Reaction
System guided by Stochastic Distances | cs.CV | We propose a new method for PolSAR (Polarimetric Synthetic Aperture Radar)
imagery classification based on stochastic distances in the space of random
matrices obeying complex Wishart distributions. Given a collection of
prototypes $\{Z_m\}_{m=1}^M$ and a stochastic distance $d(.,.)$, we classify
any random matrix $X$ ... | computer science |
25,304 | Hand Gesture Recognition Library | cs.CV | In this paper we have presented a hand gesture recognition library. Various
functions include detecting cluster count, cluster orientation, finger pointing
direction, etc. To use these functions first the input image needs to be
processed into a logical array for which a function has been developed. The
library has bee... | computer science |
25,305 | Handwriting Recognition | cs.CV | This paper describes the method to recognize offline handwritten characters.
A robust algorithm for handwriting segmentation is described here with the help
of which individual characters can be segmented from a selected word from a
paragraph of handwritten text image which is given as input. | computer science |
25,306 | Learning Complexity-Aware Cascades for Deep Pedestrian Detection | cs.CV | The design of complexity-aware cascaded detectors, combining features of very
different complexities, is considered. A new cascade design procedure is
introduced, by formulating cascade learning as the Lagrangian optimization of a
risk that accounts for both accuracy and complexity. A boosting algorithm,
denoted as com... | computer science |
25,307 | A Parameter-free Affinity Based Clustering | cs.CV | Several methods have been proposed to estimate the number of clusters in a
dataset; the basic ideal behind all of them has been to study an index that
measures inter-cluster separation and intra-cluster cohesion over a range of
cluster numbers and report the number which gives an optimum value of the
index. In this pap... | computer science |
25,308 | Efficient moving point handling for incremental 3D manifold
reconstruction | cs.CV | As incremental Structure from Motion algorithms become effective, a good
sparse point cloud representing the map of the scene becomes available
frame-by-frame. From the 3D Delaunay triangulation of these points,
state-of-the-art algorithms build a manifold rough model of the scene. These
algorithms integrate incrementa... | computer science |
25,309 | Subspace Alignment Based Domain Adaptation for RCNN Detector | cs.CV | In this paper, we propose subspace alignment based domain adaptation of the
state of the art RCNN based object detector. The aim is to be able to achieve
high quality object detection in novel, real world target scenarios without
requiring labels from the target domain. While, unsupervised domain adaptation
has been st... | computer science |
25,310 | Bottom-Up and Top-Down Reasoning with Hierarchical Rectified Gaussians | cs.CV | Convolutional neural nets (CNNs) have demonstrated remarkable performance in
recent history. Such approaches tend to work in a unidirectional bottom-up
feed-forward fashion. However, practical experience and biological evidence
tells us that feedback plays a crucial role, particularly for detailed spatial
understanding... | computer science |
25,311 | An End-to-End Trainable Neural Network for Image-based Sequence
Recognition and Its Application to Scene Text Recognition | cs.CV | Image-based sequence recognition has been a long-standing research topic in
computer vision. In this paper, we investigate the problem of scene text
recognition, which is among the most important and challenging tasks in
image-based sequence recognition. A novel neural network architecture, which
integrates feature ext... | computer science |
25,312 | Rule Of Thumb: Deep derotation for improved fingertip detection | cs.CV | We investigate a novel global orientation regression approach for articulated
objects using a deep convolutional neural network. This is integrated with an
in-plane image derotation scheme, DeROT, to tackle the problem of per-frame
fingertip detection in depth images. The method reduces the complexity of
learning in th... | computer science |
25,313 | Online Metric-Weighted Linear Representations for Robust Visual Tracking | cs.CV | In this paper, we propose a visual tracker based on a metric-weighted linear
representation of appearance. In order to capture the interdependence of
different feature dimensions, we develop two online distance metric learning
methods using proximity comparison information and structured output learning.
The learned me... | computer science |
25,314 | Every Moment Counts: Dense Detailed Labeling of Actions in Complex
Videos | cs.CV | Every moment counts in action recognition. A comprehensive understanding of
human activity in video requires labeling every frame according to the actions
occurring, placing multiple labels densely over a video sequence. To study this
problem we extend the existing THUMOS dataset and introduce MultiTHUMOS, a new
datase... | computer science |
25,315 | The Cumulative Distribution Transform and Linear Pattern Classification | cs.CV | Discriminating data classes emanating from sensors is an important problem
with many applications in science and technology. We describe a new transform
for pattern identification that interprets patterns as probability density
functions, and has special properties with regards to classification. The
transform, which w... | computer science |
25,316 | Towards Storytelling from Visual Lifelogging: An Overview | cs.CV | Visual lifelogging consists of acquiring images that capture the daily
experiences of the user by wearing a camera over a long period of time. The
pictures taken offer considerable potential for knowledge mining concerning how
people live their lives, hence, they open up new opportunities for many
potential application... | computer science |
25,317 | Data-free parameter pruning for Deep Neural Networks | cs.CV | Deep Neural nets (NNs) with millions of parameters are at the heart of many
state-of-the-art computer vision systems today. However, recent works have
shown that much smaller models can achieve similar levels of performance. In
this work, we address the problem of pruning parameters in a trained NN model.
Instead of re... | computer science |
25,318 | Bayesian Time-of-Flight for Realtime Shape, Illumination and Albedo | cs.CV | We propose a computational model for shape, illumination and albedo inference
in a pulsed time-of-flight (TOF) camera. In contrast to TOF cameras based on
phase modulation, our camera enables general exposure profiles. This results in
added flexibility and requires novel computational approaches.
To address this chal... | computer science |
25,319 | Particle detection and tracking in fluorescence time-lapse imaging: a
contrario approach | cs.CV | This paper proposes a probabilistic approach for the detection and the
tracking of particles in fluorescent time-lapse imaging. In the presence of a
very noised and poor-quality data, particles and trajectories can be
characterized by an a contrario model, that estimates the probability of
observing the structures of i... | computer science |
25,320 | Part Localization using Multi-Proposal Consensus for Fine-Grained
Categorization | cs.CV | We present a simple deep learning framework to simultaneously predict
keypoint locations and their respective visibilities and use those to achieve
state-of-the-art performance for fine-grained classification. We show that by
conditioning the predictions on object proposals with sufficient image support,
our method can... | computer science |
25,321 | Multi-Target Tracking with Time-Varying Clutter Rate and Detection
Profile: Application to Time-lapse Cell Microscopy Sequences | cs.CV | Quantitative analysis of the dynamics of tiny cellular and sub-cellular
structures, known as particles, in time-lapse cell microscopy sequences
requires the development of a reliable multi-target tracking method capable of
tracking numerous similar targets in the presence of high levels of noise, high
target density, c... | computer science |
25,322 | Deep Fishing: Gradient Features from Deep Nets | cs.CV | Convolutional Networks (ConvNets) have recently improved image recognition
performance thanks to end-to-end learning of deep feed-forward models from raw
pixels. Deep learning is a marked departure from the previous state of the art,
the Fisher Vector (FV), which relied on gradient-based encoding of local
hand-crafted ... | computer science |
25,323 | Active skeleton for bacteria modeling | cs.CV | The investigation of spatio-temporal dynamics of bacterial cells and their
molecular components requires automated image analysis tools to track cell
shape properties and molecular component locations inside the cells. In the
study of bacteria aging, the molecular components of interest are protein
aggregates accumulat... | computer science |
25,324 | Fourier descriptors based on the structure of the human primary visual
cortex with applications to object recognition | cs.CV | In this paper we propose a supervised object recognition method using new
global features and inspired by the model of the human primary visual cortex V1
as the semidiscrete roto-translation group $SE(2,N) = \mathbb Z_N\rtimes
\mathbb R^2$. The proposed technique is based on generalized Fourier
descriptors on the latte... | computer science |
25,325 | Descriptors and regions of interest fusion for gender classification in
the wild. Comparison and combination with Convolutional Neural Networks | cs.CV | Gender classification (GC) has achieved high accuracy in different
experimental evaluations based mostly on inner facial details. However, these
results do not generalize well in unrestricted datasets and particularly in
cross-database experiments, where the performance drops drastically. In this
paper, we analyze the ... | computer science |
25,326 | Efficient Face Alignment via Locality-constrained Representation for
Robust Recognition | cs.CV | Practical face recognition has been studied in the past decades, but still
remains an open challenge. Current prevailing approaches have already achieved
substantial breakthroughs in recognition accuracy. However, their performance
usually drops dramatically if face samples are severely misaligned. To address
this prob... | computer science |
25,327 | A Study of Morphological Filtering Using Graph and Hypergraphs | cs.CV | Mathematical morphology (MM) helps to describe and analyze shapes using set
theory. MM can be effectively applied to binary images which are treated as
sets. Basic morphological operators defined can be used as an effective tool in
image processing. Morphological operators are also developed based on graph and
hypergra... | computer science |
25,328 | Thinning Algorithm Using Hypergraph Based Morphological Operators | cs.CV | The object recognition is a complex problem in the image processing.
Mathematical morphology is Shape oriented operations, that simplify image data,
preserving their essential shape characteristics and eliminating irrelevancies.
This paper briefly describes morphological operators using hypergraph and its
applications ... | computer science |
25,329 | Capturing the Dynamics of Pedestrian Traffic Using a Machine Vision
System | cs.CV | We developed a machine vision system to automatically capture the dynamics of
pedestrians under four different traffic scenarios. By considering the overhead
view of each pedestrian as a digital object, the system processes the image
sequences to track the pedestrians. Considering the perspective effect of the
camera l... | computer science |
25,330 | Face Search at Scale: 80 Million Gallery | cs.CV | Due to the prevalence of social media websites, one challenge facing computer
vision researchers is to devise methods to process and search for persons of
interest among the billions of shared photos on these websites. Facebook
revealed in a 2013 white paper that its users have uploaded more than 250
billion photos, an... | computer science |
25,331 | Discovery of Shared Semantic Spaces for Multi-Scene Video Query and
Summarization | cs.CV | The growing rate of public space CCTV installations has generated a need for
automated methods for exploiting video surveillance data including scene
understanding, query, behaviour annotation and summarization. For this reason,
extensive research has been performed on surveillance scene understanding and
analysis. How... | computer science |
25,332 | Real-time 2D/3D Registration via CNN Regression | cs.CV | In this paper, we present a Convolutional Neural Network (CNN) regression
approach for real-time 2-D/3-D registration. Different from optimization-based
methods, which iteratively optimize the transformation parameters over a
scalar-valued metric function representing the quality of the registration, the
proposed metho... | computer science |
25,333 | Fast Segmentation of Left Ventricle in CT Images by Explicit Shape
Regression using Random Pixel Difference Features | cs.CV | Recently, machine learning has been successfully applied to model-based left
ventricle (LV) segmentation. The general framework involves two stages, which
starts with LV localization and is followed by boundary delineation. Both are
driven by supervised learning techniques. When compared to previous
non-learning-based ... | computer science |
25,334 | Relating Cascaded Random Forests to Deep Convolutional Neural Networks
for Semantic Segmentation | cs.CV | We consider the task of pixel-wise semantic segmentation given a small set of
labeled training images. Among two of the most popular techniques to address
this task are Random Forests (RF) and Neural Networks (NN). The main
contribution of this work is to explore the relationship between two special
forms of these tech... | computer science |
25,335 | Learning 3D Deformation of Animals from 2D Images | cs.CV | Understanding how an animal can deform and articulate is essential for a
realistic modification of its 3D model. In this paper, we show that such
information can be learned from user-clicked 2D images and a template 3D model
of the target animal. We present a volumetric deformation framework that
produces a set of new ... | computer science |
25,336 | A Multi-Camera Image Processing and Visualization System for Train
Safety Assessment | cs.CV | In this paper we present a machine vision system to efficiently monitor,
analyze and present visual data acquired with a railway overhead gantry
equipped with multiple cameras. This solution aims to improve the safety of
daily life railway transportation in a two- fold manner: (1) by providing
automatic algorithms that... | computer science |
25,337 | Occlusion-Aware Object Localization, Segmentation and Pose Estimation | cs.CV | We present a learning approach for localization and segmentation of objects
in an image in a manner that is robust to partial occlusion. Our algorithm
produces a bounding box around the full extent of the object and labels pixels
in the interior that belong to the object. Like existing segmentation aware
detection appr... | computer science |
25,338 | Adapted sampling for 3D X-ray computed tomography | cs.CV | In this paper, we introduce a method to build an adapted mesh representation
of a 3D object for X-Ray tomography reconstruction. Using this representation,
we provide means to reduce the computational cost of reconstruction by way of
iterative algorithms. The adapted sampling of the reconstruction space is
directly obt... | computer science |
25,339 | Collaborative Representation Classification Ensemble for Face
Recognition | cs.CV | Collaborative Representation Classification (CRC) for face recognition
attracts a lot attention recently due to its good recognition performance and
fast speed. Compared to Sparse Representation Classification (SRC), CRC
achieves a comparable recognition performance with 10-1000 times faster speed.
In this paper, we pr... | computer science |
25,340 | Cross-pose Face Recognition by Canonical Correlation Analysis | cs.CV | The pose problem is one of the bottlenecks in automatic face recognition. We
argue that one of the diffculties in this problem is the severe misalignment in
face images or feature vectors with different poses. In this paper, we propose
that this problem can be statistically solved or at least mitigated by
maximizing th... | computer science |
25,341 | Tracking Randomly Moving Objects on Edge Box Proposals | cs.CV | Most tracking-by-detection methods employ a local search window around the
predicted object location in the current frame assuming the previous location
is accurate, the trajectory is smooth, and the computational capacity permits a
search radius that can accommodate the maximum speed yet small enough to reduce
mismatc... | computer science |
25,342 | Fast Robust PCA on Graphs | cs.CV | Mining useful clusters from high dimensional data has received significant
attention of the computer vision and pattern recognition community in the
recent years. Linear and non-linear dimensionality reduction has played an
important role to overcome the curse of dimensionality. However, often such
methods are accompan... | computer science |
25,343 | Beamforming through regularized inverse problems in ultrasound medical
imaging | cs.CV | Beamforming in ultrasound imaging has significant impact on the quality of
the final image, controlling its resolution and contrast. Despite its low
spatial resolution and contrast, delay-and-sum is still extensively used
nowadays in clinical applications, due to its real-time capabilities. The most
common alternatives... | computer science |
25,344 | Action recognition in still images by latent superpixel classification | cs.CV | Action recognition from still images is an important task of computer vision
applications such as image annotation, robotic navigation, video surveillance
and several others. Existing approaches mainly rely on either bag-of-feature
representations or articulated body-part models. However, the relationship
between the a... | computer science |
25,345 | When VLAD met Hilbert | cs.CV | Vectors of Locally Aggregated Descriptors (VLAD) have emerged as powerful
image/video representations that compete with or even outperform
state-of-the-art approaches on many challenging visual recognition tasks. In
this paper, we address two fundamental limitations of VLAD: its requirement for
the local descriptors to... | computer science |
25,346 | Multilinear Map Layer: Prediction Regularization by Structural
Constraint | cs.CV | In this paper we propose and study a technique to impose structural
constraints on the output of a neural network, which can reduce amount of
computation and number of parameters besides improving prediction accuracy when
the output is known to approximately conform to the low-rankness prior. The
technique proceeds by ... | computer science |
25,347 | People Counting in High Density Crowds from Still Images | cs.CV | We present a method of estimating the number of people in high density crowds
from still images. The method estimates counts by fusing information from
multiple sources. Most of the existing work on crowd counting deals with very
small crowds (tens of individuals) and use temporal information from videos.
Our method us... | computer science |
25,348 | Beyond Gauss: Image-Set Matching on the Riemannian Manifold of PDFs | cs.CV | State-of-the-art image-set matching techniques typically implicitly model
each image-set with a Gaussian distribution. Here, we propose to go beyond
these representations and model image-sets as probability distribution
functions (PDFs) using kernel density estimators. To compare and match
image-sets, we exploit Csisza... | computer science |
25,349 | Flip-Rotate-Pooling Convolution and Split Dropout on Convolution Neural
Networks for Image Classification | cs.CV | This paper presents a new version of Dropout called Split Dropout (sDropout)
and rotational convolution techniques to improve CNNs' performance on image
classification. The widely used standard Dropout has advantage of preventing
deep neural networks from overfitting by randomly dropping units during
training. Our sDro... | computer science |
25,350 | Multimodal Multipart Learning for Action Recognition in Depth Videos | cs.CV | The articulated and complex nature of human actions makes the task of action
recognition difficult. One approach to handle this complexity is dividing it to
the kinetics of body parts and analyzing the actions based on these partial
descriptors. We propose a joint sparse regression based learning method which
utilizes ... | computer science |
25,351 | Deep Networks for Image Super-Resolution with Sparse Prior | cs.CV | Deep learning techniques have been successfully applied in many areas of
computer vision, including low-level image restoration problems. For image
super-resolution, several models based on deep neural networks have been
recently proposed and attained superior performance that overshadows all
previous handcrafted model... | computer science |
25,352 | Land Use Classification in Remote Sensing Images by Convolutional Neural
Networks | cs.CV | We explore the use of convolutional neural networks for the semantic
classification of remote sensing scenes. Two recently proposed architectures,
CaffeNet and GoogLeNet, are adopted, with three different learning modalities.
Besides conventional training from scratch, we resort to pre-trained networks
that are only fi... | computer science |
25,353 | Towards Distortion-Predictable Embedding of Neural Networks | cs.CV | Current research in Computer Vision has shown that Convolutional Neural
Networks (CNN) give state-of-the-art performance in many classification tasks
and Computer Vision problems. The embedding of CNN, which is the internal
representation produced by the last layer, can indirectly learn topological and
relational prope... | computer science |
25,354 | Indexing of CNN Features for Large Scale Image Search | cs.CV | The convolutional neural network (CNN) features can give a good description
of image content, which usually represent images with unique global vectors.
Although they are compact compared to local descriptors, they still cannot
efficiently deal with large-scale image retrieval due to the cost of the linear
incremental ... | computer science |
25,355 | Partial matching face recognition method for rehabilitation nursing
robots beds | cs.CV | In order to establish face recognition system in rehabilitation nursing
robots beds and achieve real-time monitor the patient on the bed. We propose a
face recognition method based on partial matching Hu moments which apply for
rehabilitation nursing robots beds. Firstly we using Haar classifier to detect
human faces a... | computer science |
25,356 | Recurrent Network Models for Human Dynamics | cs.CV | We propose the Encoder-Recurrent-Decoder (ERD) model for recognition and
prediction of human body pose in videos and motion capture. The ERD model is a
recurrent neural network that incorporates nonlinear encoder and decoder
networks before and after recurrent layers. We test instantiations of ERD
architectures in the ... | computer science |
25,357 | Dictionary and Image Recovery from Incomplete and Random Measurements | cs.CV | This paper tackles algorithmic and theoretical aspects of dictionary learning
from incomplete and random block-wise image measurements and the performance of
the adaptive dictionary for sparse image recovery. This problem is related to
blind compressed sensing in which the sparsifying dictionary or basis is viewed
as a... | computer science |
25,358 | On Hyperspectral Classification in the Compressed Domain | cs.CV | In this paper, we study the problem of hyperspectral pixel classification
based on the recently proposed architectures for compressive whisk-broom
hyperspectral imagers without the need to reconstruct the complete data cube. A
clear advantage of classification in the compressed domain is its suitability
for real-time o... | computer science |
25,359 | Local Color Contrastive Descriptor for Image Classification | cs.CV | Image representation and classification are two fundamental tasks towards
multimedia content retrieval and understanding. The idea that shape and texture
information (e.g. edge or orientation) are the key features for visual
representation is ingrained and dominated in current multimedia and computer
vision communities... | computer science |
25,360 | Kernelized Multiview Projection | cs.CV | Conventional vision algorithms adopt a single type of feature or a simple
concatenation of multiple features, which is always represented in a
high-dimensional space. In this paper, we propose a novel unsupervised spectral
embedding algorithm called Kernelized Multiview Projection (KMP) to better fuse
and embed differe... | computer science |
25,361 | Evaluating software-based fingerprint liveness detection using
Convolutional Networks and Local Binary Patterns | cs.CV | With the growing use of biometric authentication systems in the past years,
spoof fingerprint detection has become increasingly important. In this work, we
implement and evaluate two different feature extraction techniques for
software-based fingerprint liveness detection: Convolutional Networks with
random weights and... | computer science |
25,362 | Online Domain Adaptation for Multi-Object Tracking | cs.CV | Automatically detecting, labeling, and tracking objects in videos depends
first and foremost on accurate category-level object detectors. These might,
however, not always be available in practice, as acquiring high-quality large
scale labeled training datasets is either too costly or impractical for all
possible real-w... | computer science |
25,363 | Semantic Pose using Deep Networks Trained on Synthetic RGB-D | cs.CV | In this work we address the problem of indoor scene understanding from RGB-D
images. Specifically, we propose to find instances of common furniture classes,
their spatial extent, and their pose with respect to generalized class models.
To accomplish this, we use a deep, wide, multi-output convolutional neural
network (... | computer science |
25,364 | 3D Automatic Segmentation Method for Retinal Optical Coherence
Tomography Volume Data Using Boundary Surface Enhancement | cs.CV | With the introduction of spectral-domain optical coherence tomography
(SDOCT), much larger image datasets are routinely acquired compared to what was
possible using the previous generation of time-domain OCT. Thus, there is a
critical need for the development of 3D segmentation methods for processing
these data. We pre... | computer science |
25,365 | Single and Multiple Illuminant Estimation Using Convolutional Neural
Networks | cs.CV | In this paper we present a method for the estimation of the color of the
illuminant in RAW images. The method includes a Convolutional Neural Network
that has been specially designed to produce multiple local estimates. A
multiple illuminant detector determines whether or not the local outputs of the
network must be ag... | computer science |
25,366 | On the convergence of the sparse possibilistic c-means algorithm | cs.CV | In this paper, a convergence proof for the recently proposed sparse
possibilistic c-means (SPCM) algorithm is provided, utilizing the celebrated
Zangwill convergence theorem. It is shown that the iterative sequence generated
by SPCM converges to a stationary point or there exists a subsequence of it
that converges to a... | computer science |
25,367 | Detection of Critical Number of People in Interlocked Doors for Security
Access Control by Exploiting a Microwave Transceiver-Array | cs.CV | Counting the number of people is something many security application focus
on, when dealing with controlling accesses in restricted areas, as it occurs
with banks, airports, railway stations and governmental offices. This paper
presents an automated solution for detecting the presence of more than one
person into inter... | computer science |
25,368 | Evaluating color texture descriptors under large variations of
controlled lighting conditions | cs.CV | The recognition of color texture under varying lighting conditions is still
an open issue. Several features have been proposed for this purpose, ranging
from traditional statistical descriptors to features extracted with neural
networks. Still, it is not completely clear under what circumstances a feature
performs bett... | computer science |
25,369 | Partitioned Shape Modeling with On-the-Fly Sparse Appearance Learning
for Anterior Visual Pathway Segmentation | cs.CV | MRI quantification of cranial nerves such as anterior visual pathway (AVP) in
MRI is challenging due to their thin small size, structural variation along its
path, and adjacent anatomic structures. Segmentation of pathologically abnormal
optic nerve (e.g. optic nerve glioma) poses additional challenges due to
changes i... | computer science |
25,370 | Socially Constrained Structural Learning for Groups Detection in Crowd | cs.CV | Modern crowd theories agree that collective behavior is the result of the
underlying interactions among small groups of individuals. In this work, we
propose a novel algorithm for detecting social groups in crowds by means of a
Correlation Clustering procedure on people trajectories. The affinity between
crowd members ... | computer science |
25,371 | HFirst: A Temporal Approach to Object Recognition | cs.CV | This paper introduces a spiking hierarchical model for object recognition
which utilizes the precise timing information inherently present in the output
of biologically inspired asynchronous Address Event Representation (AER) vision
sensors. The asynchronous nature of these systems frees computation and
communication f... | computer science |
25,372 | TabletGaze: Unconstrained Appearance-based Gaze Estimation in Mobile
Tablets | cs.CV | We study gaze estimation on tablets, our key design goal is uncalibrated gaze
estimation using the front-facing camera during natural use of tablets, where
the posture and method of holding the tablet is not constrained. We collected
the first large unconstrained gaze dataset of tablet users, labeled Rice
TabletGaze da... | computer science |
25,373 | Compact Convolutional Neural Network Cascade for Face Detection | cs.CV | The problem of faces detection in images or video streams is a classical
problem of computer vision. The multiple solutions of this problem have been
proposed, but the question of their optimality is still open. Many algorithms
achieve a high quality face detection, but at the cost of high computational
complexity. Thi... | computer science |
25,374 | Automatic 3D Liver Segmentation Using Sparse Representation of Global
and Local Image Information via Level Set Formulation | cs.CV | In this paper, a novel framework for automated liver segmentation via a level
set formulation is presented. A sparse representation of both global
(region-based) and local (voxel-wise) image information is embedded in a level
set formulation to innovate a new cost function. Two dictionaries are build: A
region-based fe... | computer science |
25,375 | Places205-VGGNet Models for Scene Recognition | cs.CV | VGGNets have turned out to be effective for object recognition in still
images. However, it is unable to yield good performance by directly adapting
the VGGNet models trained on the ImageNet dataset for scene recognition. This
report describes our implementation of training the VGGNets on the large-scale
Places205 data... | computer science |
25,376 | Unconstrained Face Verification using Deep CNN Features | cs.CV | In this paper, we present an algorithm for unconstrained face verification
based on deep convolutional features and evaluate it on the newly released
IARPA Janus Benchmark A (IJB-A) dataset. The IJB-A dataset includes real-world
unconstrained faces from 500 subjects with full pose and illumination
variations which are ... | computer science |
25,377 | Digging Deep into the layers of CNNs: In Search of How CNNs Achieve View
Invariance | cs.CV | This paper is focused on studying the view-manifold structure in the feature
spaces implied by the different layers of Convolutional Neural Networks (CNN).
There are several questions that this paper aims to answer: Does the learned
CNN representation achieve viewpoint invariance? How does it achieve viewpoint
invarian... | computer science |
25,378 | Feature Learning for Interaction Activity Recognition in RGBD Videos | cs.CV | This paper proposes a human activity recognition method which is based on
features learned from 3D video data without incorporating domain knowledge. The
experiments on data collected by RGBD cameras produce results outperforming
other techniques. Our feature encoding method follows the bag-of-visual-word
model, then w... | computer science |
25,379 | Gait Assessment for Multiple Sclerosis Patients Using Microsoft Kinect | cs.CV | Gait analysis of patients with neurological disorders, including multiple
sclerosis (MS), is important for rehabilitation and treatment. The Mircrosoft
Kinect sensor, which was developed for motion recognition in gaming
applications, is an ideal candidate for an inexpensive system providing the
capability for human gai... | computer science |
25,380 | InAR:Inverse Augmented Reality | cs.CV | Augmented reality is the art to seamlessly fuse virtual objects into real
ones. In this short note, we address the opposite problem, the inverse
augmented reality, that is, given a perfectly augmented reality scene where
human is unable to distinguish real objects from virtual ones, how the machine
could help do the jo... | computer science |
25,381 | What is Holding Back Convnets for Detection? | cs.CV | Convolutional neural networks have recently shown excellent results in
general object detection and many other tasks. Albeit very effective, they
involve many user-defined design choices. In this paper we want to better
understand these choices by inspecting two key aspects "what did the network
learn?", and "what can ... | computer science |
25,382 | Trainable Nonlinear Reaction Diffusion: A Flexible Framework for Fast
and Effective Image Restoration | cs.CV | Image restoration is a long-standing problem in low-level computer vision
with many interesting applications. We describe a flexible learning framework
based on the concept of nonlinear reaction diffusion models for various image
restoration problems. By embodying recent improvements in nonlinear diffusion
models, we p... | computer science |
25,383 | A massively parallel multi-level approach to a domain decomposition
method for the optical flow estimation with varying illumination | cs.CV | We consider a variational method to solve the optical flow problem with
varying illumination. We apply an adaptive control of the regularization
parameter which allows us to preserve the edges and fine features of the
computed flow. To reduce the complexity of the estimation for high resolution
images and the time of c... | computer science |
25,384 | A New Approach to an Old Problem: The Reconstruction of a Go Game
through a Series of Photographs | cs.CV | Given a series of photographs taken during a Go game, we describe the
techniques we successfully employ for pinpointing the grid lines of the Go
board and for tracking their small movements between consecutive photographs;
then we discuss how to approximate the location and orientation of the
observer's point of view, ... | computer science |
25,385 | Cost Sensitive Learning of Deep Feature Representations from Imbalanced
Data | cs.CV | Class imbalance is a common problem in the case of real-world object
detection and classification tasks. Data of some classes is abundant making
them an over-represented majority, and data of other classes is scarce, making
them an under-represented minority. This imbalance makes it challenging for a
classifier to appr... | computer science |
25,386 | A Novel Approach For Finger Vein Verification Based on Self-Taught
Learning | cs.CV | In this paper, we propose a method for user Finger Vein Authentication (FVA)
as a biometric system. Using the discriminative features for classifying theses
finger veins is one of the main tips that make difference in related works,
Thus we propose to learn a set of representative features, based on
autoencoders. We mo... | computer science |
25,387 | Beat-Event Detection in Action Movie Franchises | cs.CV | While important advances were recently made towards temporally localizing and
recognizing specific human actions or activities in videos, efficient detection
and classification of long video chunks belonging to semantically defined
categories such as "pursuit" or "romance" remains challenging.We introduce a
new dataset... | computer science |
25,388 | Pose-Guided Human Parsing with Deep Learned Features | cs.CV | Parsing human body into semantic regions is crucial to human-centric
analysis. In this paper, we propose a segment-based parsing pipeline that
explores human pose information, i.e. the joint location of a human model,
which improves the part proposal, accelerates the inference and regularizes the
parsing process at the... | computer science |
25,389 | LCNN: Low-level Feature Embedded CNN for Salient Object Detection | cs.CV | In this paper, we propose a novel deep neural network framework embedded with
low-level features (LCNN) for salient object detection in complex images. We
utilise the advantage of convolutional neural networks to automatically learn
the high-level features that capture the structured information and semantic
context in... | computer science |
25,390 | Sense Beyond Expressions: Cuteness | cs.CV | With the development of Internet culture, cuteness has become a popular
concept. Many people are curious about what factors making a person look cute.
However, there is rare research to answer this interesting question. In this
work, we construct a dataset of personal images with comprehensively annotated
cuteness scor... | computer science |
25,391 | Action Recognition based on Subdivision-Fusion Model | cs.CV | This paper proposes a novel Subdivision-Fusion Model (SFM) to recognize human
actions. In most action recognition tasks, overlapping feature distribution is
a common problem leading to overfitting. In the subdivision stage of the
proposed SFM, samples in each category are clustered. Then, such samples are
grouped into ... | computer science |
25,392 | Low Rank Representation on Riemannian Manifold of Square Root Densities | cs.CV | In this paper, we present a novel low rank representation (LRR) algorithm for
data lying on the manifold of square root densities. Unlike traditional LRR
methods which rely on the assumption that the data points are vectors in the
Euclidean space, our new algorithm is designed to incorporate the intrinsic
geometric str... | computer science |
25,393 | Image tag completion by local learning | cs.CV | The problem of tag completion is to learn the missing tags of an image. In
this paper, we propose to learn a tag scoring vector for each image by local
linear learning. A local linear function is used in the neighborhood of each
image to predict the tag scoring vectors of its neighboring images. We
construct a unified ... | computer science |
25,394 | Preprint ARPPS Augmented Reality Pipeline Prospect System | cs.CV | This is the preprint version of our paper on ICONIP. Outdoor augmented
reality geographic information system (ARGIS) is the hot application of
augmented reality over recent years. This paper concludes the key solutions of
ARGIS, designs the mobile augmented reality pipeline prospect system (ARPPS),
and respectively rea... | computer science |
25,395 | A Deep Pyramid Deformable Part Model for Face Detection | cs.CV | We present a face detection algorithm based on Deformable Part Models and
deep pyramidal features. The proposed method called DP2MFD is able to detect
faces of various sizes and poses in unconstrained conditions. It reduces the
gap in training and testing of DPM on deep features by adding a normalization
layer to the d... | computer science |
25,396 | Multiresolution Approach to Acceleration of Iterative Image
Reconstruction for X-Ray Imaging for Security Applications | cs.CV | Three-dimensional x-ray CT image reconstruction in baggage scanning in
security applications is an important research field. The variety of materials
to be reconstructed is broader than medical x-ray imaging. Presence of high
attenuating materials such as metal may cause artifacts if analytical
reconstruction methods a... | computer science |
25,397 | Bit-Scalable Deep Hashing with Regularized Similarity Learning for Image
Retrieval and Person Re-identification | cs.CV | Extracting informative image features and learning effective approximate
hashing functions are two crucial steps in image retrieval . Conventional
methods often study these two steps separately, e.g., learning hash functions
from a predefined hand-crafted feature space. Meanwhile, the bit lengths of
output hashing code... | computer science |
25,398 | Learning Analysis-by-Synthesis for 6D Pose Estimation in RGB-D Images | cs.CV | Analysis-by-synthesis has been a successful approach for many tasks in
computer vision, such as 6D pose estimation of an object in an RGB-D image
which is the topic of this work. The idea is to compare the observation with
the output of a forward process, such as a rendered image of the object of
interest in a particul... | computer science |
25,399 | Saliency maps on image hierarchies | cs.CV | In this paper we propose two saliency models for salient object segmentation
based on a hierarchical image segmentation, a tree-like structure that
represents regions at different scales from the details to the whole image
(e.g. gPb-UCM, BPT). The first model is based on a hierarchy of image
partitions. The saliency at... | computer science |
25,400 | Recursive Training of 2D-3D Convolutional Networks for Neuronal Boundary
Detection | cs.CV | Efforts to automate the reconstruction of neural circuits from 3D electron
microscopic (EM) brain images are critical for the field of connectomics. An
important computation for reconstruction is the detection of neuronal
boundaries. Images acquired by serial section EM, a leading 3D EM technique,
are highly anisotropi... | computer science |
25,401 | Introducing Geometry in Active Learning for Image Segmentation | cs.CV | We propose an Active Learning approach to training a segmentation classifier
that exploits geometric priors to streamline the annotation process in 3D image
volumes. To this end, we use these priors not only to select voxels most in
need of annotation but to guarantee that they lie on 2D planar patch, which
makes it mu... | computer science |
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