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24,402 | Skin Texture Recognition Using Neural Networks | cs.CV | Skin recognition is used in many applications ranging from algorithms for
face detection, hand gesture analysis, and to objectionable image filtering. In
this work a skin recognition system was developed and tested. While many skin
segmentation algorithms relay on skin color, our work relies on both skin color
and text... | computer science |
24,403 | Stitched Panoramas from Toy Airborne Video Cameras | cs.CV | Effective panoramic photographs are taken from vantage points that are high.
High vantage points have recently become easier to reach as the cost of
quadrotor helicopters has dropped to nearly disposable levels. Although cameras
carried by such aircraft weigh only a few grams, their low-quality video can be
converted i... | computer science |
24,404 | Hilditchs Algorithm Based Tamil Character Recognition | cs.CV | Character identification plays a vital role in the contemporary world of
Image processing. It can solve many composite problems and makes humans work
easier. An instance is Handwritten Character detection. Handwritten recognition
is not a novel expertise, but it has not gained community notice until Now. The
eventual a... | computer science |
24,405 | Detection of Partially Visible Objects | cs.CV | An "elephant in the room" for most current object detection and localization
methods is the lack of explicit modelling of partial visibility due to
occlusion by other objects or truncation by the image boundary. Based on a
sliding window approach, we propose a detection method which explicitly models
partial visibility... | computer science |
24,406 | Modeling Radiometric Uncertainty for Vision with Tone-mapped Color
Images | cs.CV | To produce images that are suitable for display, tone-mapping is widely used
in digital cameras to map linear color measurements into narrow gamuts with
limited dynamic range. This introduces non-linear distortion that must be
undone, through a radiometric calibration process, before computer vision
systems can analyze... | computer science |
24,407 | A novel framework for image forgery localization | cs.CV | Image forgery localization is a very active and open research field for the
difficulty to handle the large variety of manipulations a malicious user can
perform by means of more and more sophisticated image editing tools. Here, we
propose a localization framework based on the fusion of three very different
tools, based... | computer science |
24,408 | Image forgery detection based on the fusion of machine learning and
block-matching methods | cs.CV | Dense local descriptors and machine learning have been used with success in
several applications, like classification of textures, steganalysis, and
forgery detection. We develop a new image forgery detector building upon some
descriptors recently proposed in the steganalysis field suitably merging some
of such descrip... | computer science |
24,409 | A Novel Illumination-Invariant Loss for Monocular 3D Pose Estimation | cs.CV | The problem of identifying the 3D pose of a known object from a given 2D
image has important applications in Computer Vision. Our proposed method of
registering a 3D model of a known object on a given 2D photo of the object has
numerous advantages over existing methods. It does not require prior training,
knowledge of ... | computer science |
24,410 | Unobtrusive Low Cost Pupil Size Measurements using Web cameras | cs.CV | Unobtrusive every day health monitoring can be of important use for the
elderly population. In particular, pupil size may be a valuable source of
information, since, apart from pathological cases, it can reveal the emotional
state, the fatigue and the ageing. To allow for unobtrusive monitoring to gain
acceptance, one ... | computer science |
24,411 | Improving Texture Categorization with Biologically Inspired Filtering | cs.CV | Within the domain of texture classification, a lot of effort has been spent
on local descriptors, leading to many powerful algorithms. However,
preprocessing techniques have received much less attention despite their
important potential for improving the overall classification performance. We
address this question by p... | computer science |
24,412 | Template-Based Active Contours | cs.CV | We develop a generalized active contour formalism for image segmentation
based on shape templates. The shape template is subjected to a restricted
affine transformation (RAT) in order to segment the object of interest. RAT
allows for translation, rotation, and scaling, which give a total of five
degrees of freedom. The... | computer science |
24,413 | Feature Extraction of Human Lip Prints | cs.CV | Methods have been used for identification of human by recognizing lip prints.
Human lips have a number of elevation and depressions features called lip
prints and examination of lip prints is referred to as cheiloscopy. Lip prints
of each human being are unique in nature like many others features of human. In
this pape... | computer science |
24,414 | Multi-Sensor Image Fusion Based on Moment Calculation | cs.CV | An image fusion method based on salient features is proposed in this paper.
In this work, we have concentrated on salient features of the image for fusion
in order to preserve all relevant information contained in the input images and
tried to enhance the contrast in fused image and also suppressed noise to a
maximum e... | computer science |
24,415 | Geometric Feature Based Face-Sketch Recognition | cs.CV | This paper presents a novel facial sketch image or face-sketch recognition
approach based on facial feature extraction. To recognize a face-sketch, we
have concentrated on a set of geometric face features like eyes, nose,
eyebrows, lips, etc and their length and width ratio because it is difficult to
match photos and s... | computer science |
24,416 | An adaptive block based integrated LDP,GLCM,and Morphological features
for Face Recognition | cs.CV | This paper proposes a technique for automatic face recognition using
integrated multiple feature sets extracted from the significant blocks of a
gradient image. We discuss about the use of novel morphological, local
directional pattern (LDP) and gray-level co-occurrence matrix GLCM based
feature extraction technique to... | computer science |
24,417 | A Gabor block based Kernel Discriminative Common Vector (KDCV) approach
using cosine kernels for Human Face Recognition | cs.CV | In this paper a nonlinear Gabor Wavelet Transform (GWT) discriminant feature
extraction approach for enhanced face recognition is proposed. Firstly, the
low-energized blocks from Gabor wavelet transformed images are extracted.
Secondly, the nonlinear discriminating features are analyzed and extracted from
the selected ... | computer science |
24,418 | A Face Recognition approach based on entropy estimate of the nonlinear
DCT features in the Logarithm Domain together with Kernel Entropy Component
Analysis | cs.CV | This paper exploits the feature extraction capabilities of the discrete
cosine transform (DCT) together with an illumination normalization approach in
the logarithm domain that increase its robustness to variations in facial
geometry and illumination. Secondly in the same domain the entropy measures are
applied on the ... | computer science |
24,419 | An Approach: Modality Reduction and Face-Sketch Recognition | cs.CV | To recognize face sketch through face photo database is a challenging task
for todays researchers. Because face photo images in training set and face
sketch images in testing set have different modality. Difference between two
face photos of difference person is smaller than the difference between same
person in a face... | computer science |
24,420 | Face Recognition using Hough Peaks extracted from the significant blocks
of the Gradient Image | cs.CV | This paper proposes a new technique for automatic face recognition using
integrated peaks of the Hough transformed significant blocks of the binary
gradient image. In this approach firstly the gradient of an image is calculated
and a threshold is set to obtain a binary gradient image, which is less
sensitive to noise a... | computer science |
24,421 | High Performance Human Face Recognition using Gabor based Pseudo Hidden
Markov Model | cs.CV | This paper introduces a novel methodology that combines the multi-resolution
feature of the Gabor wavelet transformation (GWT) with the local interactions
of the facial structures expressed through the Pseudo Hidden Markov model
(PHMM). Unlike the traditional zigzag scanning method for feature extraction a
continuous s... | computer science |
24,422 | Human Face Recognition using Gabor based Kernel Entropy Component
Analysis | cs.CV | In this paper, we present a novel Gabor wavelet based Kernel Entropy
Component Analysis (KECA) method by integrating the Gabor wavelet
transformation (GWT) of facial images with the KECA method for enhanced face
recognition performance. Firstly, from the Gabor wavelet transformed images the
most important discriminativ... | computer science |
24,423 | Multi-frame denoising of high speed optical coherence tomography data
using inter-frame and intra-frame priors | cs.CV | Optical coherence tomography (OCT) is an important interferometric diagnostic
technique which provides cross-sectional views of the subsurface microstructure
of biological tissues. However, the imaging quality of high-speed OCT is
limited due to the large speckle noise. To address this problem, this paper
proposes a mu... | computer science |
24,424 | On the Performance of Filters for Reduction of Speckle Noise in SAR
Images off the Coast of the Gulf of Guinea | cs.CV | Synthetic Aperture Radar (SAR) imagery to monitor oil spills are some methods
that have been proposed for the West African sub-region. With the increase in
the number of oil exploration companies in Ghana (and her neighbors) and the
rise in the coastal activities in the sub-region, there is the need for proper
monitori... | computer science |
24,425 | Heat kernel coupling for multiple graph analysis | cs.CV | In this paper, we introduce heat kernel coupling (HKC) as a method of
constructing multimodal spectral geometry on weighted graphs of different size
without vertex-wise bijective correspondence. We show that Laplacian averaging
can be derived as a limit case of HKC, and demonstrate its applications on
several problems ... | computer science |
24,426 | Fast Approximate $K$-Means via Cluster Closures | cs.CV | $K$-means, a simple and effective clustering algorithm, is one of the most
widely used algorithms in multimedia and computer vision community. Traditional
$k$-means is an iterative algorithm---in each iteration new cluster centers are
computed and each data point is re-assigned to its nearest center. The cluster
re-ass... | computer science |
24,427 | Fast Neighborhood Graph Search using Cartesian Concatenation | cs.CV | In this paper, we propose a new data structure for approximate nearest
neighbor search. This structure augments the neighborhood graph with a bridge
graph. We propose to exploit Cartesian concatenation to produce a large set of
vectors, called bridge vectors, from several small sets of subvectors. Each
bridge vector is... | computer science |
24,428 | Thickness Mapping of Eleven Retinal Layers in Normal Eyes Using Spectral
Domain Optical Coherence Tomography | cs.CV | Purpose. This study was conducted to determine the thickness map of eleven
retinal layers in normal subjects by spectral domain optical coherence
tomography (SD-OCT) and evaluate their association with sex and age. Methods.
Mean regional retinal thickness of 11 retinal layers were obtained by automatic
three-dimensiona... | computer science |
24,429 | Associative embeddings for large-scale knowledge transfer with
self-assessment | cs.CV | We propose a method for knowledge transfer between semantically related
classes in ImageNet. By transferring knowledge from the images that have
bounding-box annotations to the others, our method is capable of automatically
populating ImageNet with many more bounding-boxes and even pixel-level
segmentations. The underl... | computer science |
24,430 | Analysis and Understanding of Various Models for Efficient
Representation and Accurate Recognition of Human Faces | cs.CV | In this paper we have tried to compare the various face recognition models
against their classical problems. We look at the methods followed by these
approaches and evaluate to what extent they are able to solve the problems. All
methods proposed have some drawbacks under certain conditions. To overcome
these drawbacks... | computer science |
24,431 | Clustering using Vector Membership: An Extension of the Fuzzy C-Means
Algorithm | cs.CV | Clustering is an important facet of explorative data mining and finds
extensive use in several fields. In this paper, we propose an extension of the
classical Fuzzy C-Means clustering algorithm. The proposed algorithm,
abbreviated as VFC, adopts a multi-dimensional membership vector for each data
point instead of the t... | computer science |
24,432 | A robust Iris recognition method on adverse conditions | cs.CV | As a stable biometric system, iris has recently attracted great attention
among the researchers. However, research is still needed to provide appropriate
solutions to ensure the resistance of the system against error factors. The
present study has tried to apply a mask to the image so that the unexpected
factors affect... | computer science |
24,433 | One-Shot-Learning Gesture Recognition using HOG-HOF Features | cs.CV | The purpose of this paper is to describe one-shot-learning gesture
recognition systems developed on the \textit{ChaLearn Gesture Dataset}. We use
RGB and depth images and combine appearance (Histograms of Oriented Gradients)
and motion descriptors (Histogram of Optical Flow) for parallel temporal
segmentation and recog... | computer science |
24,434 | DeepPose: Human Pose Estimation via Deep Neural Networks | cs.CV | We propose a method for human pose estimation based on Deep Neural Networks
(DNNs). The pose estimation is formulated as a DNN-based regression problem
towards body joints. We present a cascade of such DNN regressors which results
in high precision pose estimates. The approach has the advantage of reasoning
about pose ... | computer science |
24,435 | Learning High-level Image Representation for Image Retrieval via
Multi-Task DNN using Clickthrough Data | cs.CV | Image retrieval refers to finding relevant images from an image database for
a query, which is considered difficult for the gap between low-level
representation of images and high-level representation of queries. Recently
further developed Deep Neural Network sheds light on automatically learning
high-level image repre... | computer science |
24,436 | Co-Sparse Textural Similarity for Image Segmentation | cs.CV | We propose an algorithm for segmenting natural images based on texture and
color information, which leverages the co-sparse analysis model for image
segmentation within a convex multilabel optimization framework. As a key
ingredient of this method, we introduce a novel textural similarity measure,
which builds upon the... | computer science |
24,437 | BW - Eye Ophthalmologic decision support system based on clinical
workflow and data mining techniques-image registration algorithm | cs.CV | Blueworks - Medical Expert Diagnosis is developing an application, BWEye, to
be used as an ophthalmology consultation decision support system. The
implementation of this application involves several different tasks and one of
them is the implementation of an ophthalmology images registration algorithm.
The work reporte... | computer science |
24,438 | Deep Convolutional Ranking for Multilabel Image Annotation | cs.CV | Multilabel image annotation is one of the most important challenges in
computer vision with many real-world applications. While existing work usually
use conventional visual features for multilabel annotation, features based on
Deep Neural Networks have shown potential to significantly boost performance.
In this work, ... | computer science |
24,439 | Stable Camera Motion Estimation Using Convex Programming | cs.CV | We study the inverse problem of estimating n locations $t_1, ..., t_n$ (up to
global scale, translation and negation) in $R^d$ from noisy measurements of a
subset of the (unsigned) pairwise lines that connect them, that is, from noisy
measurements of $\pm (t_i - t_j)/\|t_i - t_j\|$ for some pairs (i,j) (where the
signs... | computer science |
24,440 | Some Improvements on Deep Convolutional Neural Network Based Image
Classification | cs.CV | We investigate multiple techniques to improve upon the current state of the
art deep convolutional neural network based image classification pipeline. The
techiques include adding more image transformations to training data, adding
more transformations to generate additional predictions at test time and using
complemen... | computer science |
24,441 | An Adaptive Dictionary Learning Approach for Modeling Dynamical Textures | cs.CV | Video representation is an important and challenging task in the computer
vision community. In this paper, we assume that image frames of a moving scene
can be modeled as a Linear Dynamical System. We propose a sparse coding
framework, named adaptive video dictionary learning (AVDL), to model a video
adaptively. The de... | computer science |
24,442 | EXMOVES: Classifier-based Features for Scalable Action Recognition | cs.CV | This paper introduces EXMOVES, learned exemplar-based features for efficient
recognition of actions in videos. The entries in our descriptor are produced by
evaluating a set of movement classifiers over spatial-temporal volumes of the
input sequence. Each movement classifier is a simple exemplar-SVM trained on
low-leve... | computer science |
24,443 | Generic Deep Networks with Wavelet Scattering | cs.CV | We introduce a two-layer wavelet scattering network, for object
classification. This scattering transform computes a spatial wavelet transform
on the first layer and a new joint wavelet transform along spatial, angular and
scale variables in the second layer. Numerical experiments demonstrate that
this two layer convol... | computer science |
24,444 | Occupancy Detection in Vehicles Using Fisher Vector Image Representation | cs.CV | Due to the high volume of traffic on modern roadways, transportation agencies
have proposed High Occupancy Vehicle (HOV) lanes and High Occupancy Tolling
(HOT) lanes to promote car pooling. However, enforcement of the rules of these
lanes is currently performed by roadside enforcement officers using visual
observation.... | computer science |
24,445 | Deep Inside Convolutional Networks: Visualising Image Classification
Models and Saliency Maps | cs.CV | This paper addresses the visualisation of image classification models, learnt
using deep Convolutional Networks (ConvNets). We consider two visualisation
techniques, based on computing the gradient of the class score with respect to
the input image. The first one generates an image, which maximises the class
score [Erh... | computer science |
24,446 | Multi-digit Number Recognition from Street View Imagery using Deep
Convolutional Neural Networks | cs.CV | Recognizing arbitrary multi-character text in unconstrained natural
photographs is a hard problem. In this paper, we address an equally hard
sub-problem in this domain viz. recognizing arbitrary multi-digit numbers from
Street View imagery. Traditional approaches to solve this problem typically
separate out the localiz... | computer science |
24,447 | Multi-View Priors for Learning Detectors from Sparse Viewpoint Data | cs.CV | While the majority of today's object class models provide only 2D bounding
boxes, far richer output hypotheses are desirable including viewpoint,
fine-grained category, and 3D geometry estimate. However, models trained to
provide richer output require larger amounts of training data, preferably well
covering the releva... | computer science |
24,448 | Learning Generative Models with Visual Attention | cs.CV | Attention has long been proposed by psychologists as important for
effectively dealing with the enormous sensory stimulus available in the
neocortex. Inspired by the visual attention models in computational
neuroscience and the need of object-centric data for generative models, we
describe for generative learning frame... | computer science |
24,449 | A Review on Automated Brain Tumor Detection and Segmentation from MRI of
Brain | cs.CV | Tumor segmentation from magnetic resonance imaging (MRI) data is an important
but time consuming manual task performed by medical experts. Automating this
process is a challenging task because of the high diversity in the appearance
of tumor tissues among different patients and in many cases similarity with the
normal ... | computer science |
24,450 | Learned versus Hand-Designed Feature Representations for 3d
Agglomeration | cs.CV | For image recognition and labeling tasks, recent results suggest that machine
learning methods that rely on manually specified feature representations may be
outperformed by methods that automatically derive feature representations based
on the data. Yet for problems that involve analysis of 3d objects, such as mesh
se... | computer science |
24,451 | Extracting Region of Interest for Palm Print Authentication | cs.CV | Biometrics authentication is an effective method for automatically
recognizing individuals. The authentication consists of an enrollment phase and
an identification or verification phase. In the stages of enrollment known
(training) samples after the pre-processing stage are used for suitable feature
extraction to gene... | computer science |
24,452 | OverFeat: Integrated Recognition, Localization and Detection using
Convolutional Networks | cs.CV | We present an integrated framework for using Convolutional Networks for
classification, localization and detection. We show how a multiscale and
sliding window approach can be efficiently implemented within a ConvNet. We
also introduce a novel deep learning approach to localization by learning to
predict object boundar... | computer science |
24,453 | An Efficient Edge Detection Technique by Two Dimensional Rectangular
Cellular Automata | cs.CV | This paper proposes a new pattern of two dimensional cellular automata linear
rules that are used for efficient edge detection of an image. Since cellular
automata is inherently parallel in nature, it has produced desired output
within a unit time interval. We have observed four linear rules among 512 total
linear rule... | computer science |
24,454 | A Survey on Eye-Gaze Tracking Techniques | cs.CV | Study of eye-movement is being employed in Human Computer Interaction (HCI)
research. Eye - gaze tracking is one of the most challenging problems in the
area of computer vision. The goal of this paper is to present a review of
latest research in this continued growth of remote eye-gaze tracking. This
overview includes ... | computer science |
24,455 | Top Down Approach to Multiple Plane Detection | cs.CV | Detecting multiple planes in images is a challenging problem, but one with
many applications. Recent work such as J-Linkage and Ordered Residual Kernels
have focussed on developing a domain independent approach to detect multiple
structures. These multiple structure detection methods are then used for
estimating multip... | computer science |
24,456 | 3D Interest Point Detection via Discriminative Learning | cs.CV | The task of detecting the interest points in 3D meshes has typically been
handled by geometric methods. These methods, while greatly describing human
preference, can be ill-equipped for handling the variety and subjectivity in
human responses. Different tasks have different requirements for interest point
detection; so... | computer science |
24,457 | Face Detection from still and Video Images using Unsupervised Cellular
Automata with K means clustering algorithm | cs.CV | Pattern recognition problem rely upon the features inherent in the pattern of
images. Face detection and recognition is one of the challenging research areas
in the field of computer vision. In this paper, we present a method to identify
skin pixels from still and video images using skin color. Face regions are
identif... | computer science |
24,458 | Finding More Relevance: Propagating Similarity on Markov Random Field
for Image Retrieval | cs.CV | To effectively retrieve objects from large corpus with high accuracy is a
challenge task. In this paper, we propose a method that propagates visual
feature level similarities on a Markov random field (MRF) to obtain a high
level correspondence in image space for image pairs. The proposed
correspondence between image pa... | computer science |
24,459 | Lesion Border Detection in Dermoscopy Images Using Ensembles of
Thresholding Methods | cs.CV | Dermoscopy is one of the major imaging modalities used in the diagnosis of
melanoma and other pigmented skin lesions. Due to the difficulty and
subjectivity of human interpretation, automated analysis of dermoscopy images
has become an important research area. Border detection is often the first step
in this analysis. ... | computer science |
24,460 | Shape Primitive Histogram: A Novel Low-Level Face Representation for
Face Recognition | cs.CV | We further exploit the representational power of Haar wavelet and present a
novel low-level face representation named Shape Primitives Histogram (SPH) for
face recognition. Since human faces exist abundant shape features, we address
the face representation issue from the perspective of the shape feature
extraction. In ... | computer science |
24,461 | Collaborative Discriminant Locality Preserving Projections With its
Application to Face Recognition | cs.CV | We present a novel Discriminant Locality Preserving Projections (DLPP)
algorithm named Collaborative Discriminant Locality Preserving Projection
(CDLPP). In our algorithm, the discriminating power of DLPP are further
exploited from two aspects. On the one hand, the global optimum of class
scattering is guaranteed via u... | computer science |
24,462 | A Novel Retinal Vessel Segmentation Based On Histogram Transformation
Using 2-D Morlet Wavelet and Supervised Classification | cs.CV | The appearance and structure of blood vessels in retinal images have an
important role in diagnosis of diseases. This paper proposes a method for
automatic retinal vessel segmentation. In this work, a novel preprocessing
based on local histogram equalization is used to enhance the original image
then pixels are classif... | computer science |
24,463 | Actions in the Eye: Dynamic Gaze Datasets and Learnt Saliency Models for
Visual Recognition | cs.CV | Systems based on bag-of-words models from image features collected at maxima
of sparse interest point operators have been used successfully for both
computer visual object and action recognition tasks. While the sparse,
interest-point based approach to recognition is not inconsistent with visual
processing in biologica... | computer science |
24,464 | A Novel Method for Automatic Segmentation of Brain Tumors in MRI Images | cs.CV | The brain tumor segmentation on MRI images is a very difficult and important
task which is used in surgical and medical planning and assessments. If experts
do the segmentation manually with their own medical knowledge, it will be
time-consuming. Therefore, researchers propose methods and systems which can do
the segme... | computer science |
24,465 | Constrained Parametric Proposals and Pooling Methods for Semantic
Segmentation in RGB-D Images | cs.CV | We focus on the problem of semantic segmentation based on RGB-D data, with
emphasis on analyzing cluttered indoor scenes containing many instances from
many visual categories. Our approach is based on a parametric figure-ground
intensity and depth-constrained proposal process that generates spatial layout
hypotheses at... | computer science |
24,466 | Traffic Monitoring Using M2M Communication | cs.CV | This paper presents an intelligent traffic monitoring system using wireless
vision sensor network that captures and processes the real-time video image to
obtain the traffic flow rate and vehicle speeds along different urban roadways.
This system will display the traffic states on the front roadways that can
guide the ... | computer science |
24,467 | A Continuous Max-Flow Approach to General Hierarchical Multi-Labeling
Problems | cs.CV | Multi-region segmentation algorithms often have the onus of incorporating
complex anatomical knowledge representing spatial or geometric relationships
between objects, and general-purpose methods of addressing this knowledge in an
optimization-based manner have thus been lacking. This paper presents
Generalized Hierarc... | computer science |
24,468 | A Comparative Study of Modern Inference Techniques for Structured
Discrete Energy Minimization Problems | cs.CV | Szeliski et al. published an influential study in 2006 on energy minimization
methods for Markov Random Fields (MRF). This study provided valuable insights
in choosing the best optimization technique for certain classes of problems.
While these insights remain generally useful today, the phenomenal success of
random fi... | computer science |
24,469 | Weyl group orbit functions in image processing | cs.CV | We deal with the Fourier-like analysis of functions on discrete grids in
two-dimensional simplexes using $C-$ and $E-$ Weyl group orbit functions. For
these cases we present the convolution theorem. We provide an example of
application of image processing using the $C-$ functions and the convolutions
for spatial filter... | computer science |
24,470 | MBIS: Multivariate Bayesian Image Segmentation Tool | cs.CV | We present MBIS (Multivariate Bayesian Image Segmentation tool), a clustering
tool based on the mixture of multivariate normal distributions model. MBIS
supports multi-channel bias field correction based on a B-spline model. A
second methodological novelty is the inclusion of graph-cuts optimization for
the stationary ... | computer science |
24,471 | Extraction of Projection Profile, Run-Histogram and Entropy Features
Straight from Run-Length Compressed Text-Documents | cs.CV | Document Image Analysis, like any Digital Image Analysis requires
identification and extraction of proper features, which are generally extracted
from uncompressed images, though in reality images are made available in
compressed form for the reasons such as transmission and storage efficiency.
However, this implies th... | computer science |
24,472 | An Efficient Two-Stage Sparse Representation Method | cs.CV | There are a large number of methods for solving under-determined linear
inverse problem. Many of them have very high time complexity for large
datasets. We propose a new method called Two-Stage Sparse Representation (TSSR)
to tackle this problem. We decompose the representing space of signals into two
parts, the measur... | computer science |
24,473 | Recognition of Handwritten MODI Numerals using Hu and Zernike features | cs.CV | Handwritten automatic character recognition has attracted many researchers
all over the world to contribute automatic character recognition domain. Shape
identification and feature extraction is very important part of any character
recognition system and success of method is highly dependent on selection of
features. H... | computer science |
24,474 | Pseudo-Zernike Based Multi-Pass Automatic Target Recognition From
Multi-Channel SAR | cs.CV | The capability to exploit multiple sources of information is of fundamental
importance in a battlefield scenario. Information obtained from different
sources, and separated in space and time, provide the opportunity to exploit
diversities in order to mitigate uncertainty. For the specific challenge of
Automatic Target ... | computer science |
24,475 | Neural Codes for Image Retrieval | cs.CV | It has been shown that the activations invoked by an image within the top
layers of a large convolutional neural network provide a high-level descriptor
of the visual content of the image. In this paper, we investigate the use of
such descriptors (neural codes) within the image retrieval application. In the
experiments... | computer science |
24,476 | Improving Bilayer Product Quantization for Billion-Scale Approximate
Nearest Neighbors in High Dimensions | cs.CV | The top-performing systems for billion-scale high-dimensional approximate
nearest neighbor (ANN) search are all based on two-layer architectures that
include an indexing structure and a compressed datapoints layer. An indexing
structure is crucial as it allows to avoid exhaustive search, while the lossy
data compressio... | computer science |
24,477 | DenseNet: Implementing Efficient ConvNet Descriptor Pyramids | cs.CV | Convolutional Neural Networks (CNNs) can provide accurate object
classification. They can be extended to perform object detection by iterating
over dense or selected proposed object regions. However, the runtime of such
detectors scales as the total number and/or area of regions to examine per
image, and training such ... | computer science |
24,478 | Automatic Tracker Selection w.r.t Object Detection Performance | cs.CV | The tracking algorithm performance depends on video content. This paper
presents a new multi-object tracking approach which is able to cope with video
content variations. First the object detection is improved using Kanade-
Lucas-Tomasi (KLT) feature tracking. Second, for each mobile object, an
appropriate tracker is s... | computer science |
24,479 | Entropy Computation of Document Images in Run-Length Compressed Domain | cs.CV | Compression of documents, images, audios and videos have been traditionally
practiced to increase the efficiency of data storage and transfer. However, in
order to process or carry out any analytical computations, decompression has
become an unavoidable pre-requisite. In this research work, we have attempted
to compute... | computer science |
24,480 | Cascades of Regression Tree Fields for Image Restoration | cs.CV | Conditional random fields (CRFs) are popular discriminative models for
computer vision and have been successfully applied in the domain of image
restoration, especially to image denoising. For image deblurring, however,
discriminative approaches have been mostly lacking. We posit two reasons for
this: First, the blur k... | computer science |
24,481 | A Compact Linear Programming Relaxation for Binary Sub-modular MRF | cs.CV | We propose a novel compact linear programming (LP) relaxation for binary
sub-modular MRF in the context of object segmentation. Our model is obtained by
linearizing an $l_1^+$-norm derived from the quadratic programming (QP) form of
the MRF energy. The resultant LP model contains significantly fewer variables
and const... | computer science |
24,482 | RANCOR: Non-Linear Image Registration with Total Variation
Regularization | cs.CV | Optimization techniques have been widely used in deformable registration,
allowing for the incorporation of similarity metrics with regularization
mechanisms. These regularization mechanisms are designed to mitigate the
effects of trivial solutions to ill-posed registration problems and to
otherwise ensure the resultin... | computer science |
24,483 | A Reverse Hierarchy Model for Predicting Eye Fixations | cs.CV | A number of psychological and physiological evidences suggest that early
visual attention works in a coarse-to-fine way, which lays a basis for the
reverse hierarchy theory (RHT). This theory states that attention propagates
from the top level of the visual hierarchy that processes gist and abstract
information of inpu... | computer science |
24,484 | Shrinkage Optimized Directed Information using Pictorial Structures for
Action Recognition | cs.CV | In this paper, we propose a novel action recognition framework. The method
uses pictorial structures and shrinkage optimized directed information
assessment (SODA) coupled with Markov Random Fields called SODA+MRF to model
the directional temporal dependency and bidirectional spatial dependency. As a
variant of mutual ... | computer science |
24,485 | Learning Deep Convolutional Features for MRI Based Alzheimer's Disease
Classification | cs.CV | Effective and accurate diagnosis of Alzheimer's disease (AD) or mild
cognitive impairment (MCI) can be critical for early treatment and thus has
attracted more and more attention nowadays. Since first introduced, machine
learning methods have been gaining increasing popularity for AD related
research. Among the various... | computer science |
24,486 | Proceedings of The 38th Annual Workshop of the Austrian Association for
Pattern Recognition (ÖAGM), 2014 | cs.CV | The 38th Annual Workshop of the Austrian Association for Pattern Recognition
(\"OAGM) will be held at IST Austria, on May 22-23, 2014. The workshop provides
a platform for researchers and industry to discuss traditional and new areas of
computer vision. This year the main topic is: Pattern Recognition:
interdisciplinar... | computer science |
24,487 | Recover Canonical-View Faces in the Wild with Deep Neural Networks | cs.CV | Face images in the wild undergo large intra-personal variations, such as
poses, illuminations, occlusions, and low resolutions, which cause great
challenges to face-related applications. This paper addresses this challenge by
proposing a new deep learning framework that can recover the canonical view of
face images. It... | computer science |
24,488 | Face Detection with a 3D Model | cs.CV | This paper presents a part-based face detection approach where the spatial
relationship between the face parts is represented by a hidden 3D model with
six parameters. The computational complexity of the search in the six
dimensional pose space is addressed by proposing meaningful 3D pose candidates
by image-based regr... | computer science |
24,489 | Scalable Matting: A Sub-linear Approach | cs.CV | Natural image matting, which separates foreground from background, is a very
important intermediate step in recent computer vision algorithms. However, it
is severely underconstrained and difficult to solve. State-of-the-art
approaches include matting by graph Laplacian, which significantly improves the
underconstraine... | computer science |
24,490 | Spiralet Sparse Representation | cs.CV | This is the first report on Working Paper WP-RFM-14-01. The potential and
capability of sparse representations is well-known. However, their
(multivariate variable) vectorial form, which is completely fine in many fields
and disciplines, results in removal and filtering of important "spatial"
relations that are implici... | computer science |
24,491 | Generic Object Detection With Dense Neural Patterns and Regionlets | cs.CV | This paper addresses the challenge of establishing a bridge between deep
convolutional neural networks and conventional object detection frameworks for
accurate and efficient generic object detection. We introduce Dense Neural
Patterns, short for DNPs, which are dense local features derived from
discriminatively traine... | computer science |
24,492 | Cube-Cut: Vertebral Body Segmentation in MRI-Data through Cubic-Shaped
Divergences | cs.CV | In this article, we present a graph-based method using a cubic template for
volumetric segmentation of vertebrae in magnetic resonance imaging (MRI)
acquisitions. The user can define the degree of deviation from a regular cube
via a smoothness value Delta. The Cube-Cut algorithm generates a directed graph
with two term... | computer science |
24,493 | Learning Fine-grained Image Similarity with Deep Ranking | cs.CV | Learning fine-grained image similarity is a challenging task. It needs to
capture between-class and within-class image differences. This paper proposes a
deep ranking model that employs deep learning techniques to learn similarity
metric directly from images.It has higher learning capability than models based
on hand-c... | computer science |
24,494 | Online Group Feature Selection | cs.CV | Online feature selection with dynamic features has become an active research
area in recent years. However, in some real-world applications such as image
analysis and email spam filtering, features may arrive by groups. Existing
online feature selection methods evaluate features individually, while existing
group featu... | computer science |
24,495 | Robust Face Recognition via Adaptive Sparse Representation | cs.CV | Sparse Representation (or coding) based Classification (SRC) has gained great
success in face recognition in recent years. However, SRC emphasizes the
sparsity too much and overlooks the correlation information which has been
demonstrated to be critical in real-world face recognition problems. Besides,
some work consid... | computer science |
24,496 | Automatic Annotation of Axoplasmic Reticula in Pursuit of Connectomes | cs.CV | In this paper, we present a new pipeline which automatically identifies and
annotates axoplasmic reticula, which are small subcellular structures present
only in axons. We run our algorithm on the Kasthuri11 dataset, which was color
corrected using gradient-domain techniques to adjust contrast. We use a
bilateral filte... | computer science |
24,497 | Unified Structured Learning for Simultaneous Human Pose Estimation and
Garment Attribute Classification | cs.CV | In this paper, we utilize structured learning to simultaneously address two
intertwined problems: human pose estimation (HPE) and garment attribute
classification (GAC), which are valuable for a variety of computer vision and
multimedia applications. Unlike previous works that usually handle the two
problems separately... | computer science |
24,498 | Geometric Abstraction from Noisy Image-Based 3D Reconstructions | cs.CV | Creating geometric abstracted models from image-based scene reconstructions
is difficult due to noise and irregularities in the reconstructed model. In
this paper, we present a geometric modeling method for noisy reconstructions
dominated by planar horizontal and orthogonal vertical structures. We partition
the scene i... | computer science |
24,499 | A higher-order MRF based variational model for multiplicative noise
reduction | cs.CV | The Fields of Experts (FoE) image prior model, a filter-based higher-order
Markov Random Fields (MRF) model, has been shown to be effective for many image
restoration problems. Motivated by the successes of FoE-based approaches, in
this letter, we propose a novel variational model for multiplicative noise
reduction bas... | computer science |
24,500 | Fast Approximate Matching of Cell-Phone Videos for Robust Background
Subtraction | cs.CV | We identify a novel instance of the background subtraction problem that
focuses on extracting near-field foreground objects captured using handheld
cameras. Given two user-generated videos of a scene, one with and the other
without the foreground object(s), our goal is to efficiently generate an output
video with only ... | computer science |
24,501 | Large Margin Image Set Representation and Classification | cs.CV | In this paper, we propose a novel image set representation and classification
method by maximizing the margin of image sets. The margin of an image set is
defined as the difference of the distance to its nearest image set from
different classes and the distance to its nearest image set of the same class.
By modeling th... | computer science |
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