Unnamed: 0 int64 0 41k | title stringlengths 4 274 | category stringlengths 5 18 | summary stringlengths 22 3.66k | theme stringclasses 8
values |
|---|---|---|---|---|
24,702 | New similarity index based on entropy and group theory | cs.CV | In this work, we propose a new similarity index for images considering the
entropy function and group theory. This index considers an algebraic group of
images, it is defined by an inner law that provides a novel approach for the
subtraction of images. Through an equivalence relationship in the field of
images, we prov... | computer science |
24,703 | A hierarchical framework for object recognition | cs.CV | Object recognition in the presence of background clutter and distractors is a
central problem both in neuroscience and in machine learning. However, the
performance level of the models that are inspired by cortical mechanisms,
including deep networks such as convolutional neural networks and deep belief
networks, is sh... | computer science |
24,704 | Extended Dynamic Programming and Fast Multidimensional Search Algorithm
for Energy Minization in Stereo and Motion | cs.CV | This paper presents a novel extended dynamic programming approach for energy
minimization (EDP) to solve the correspondence problem for stereo and motion. A
significant speedup is achieved using a recursive minimum search strategy
(RMS). The mentioned speedup is particularly important if the disparity space
is 2D as we... | computer science |
24,705 | A comparison of dense region detectors for image search and fine-grained
classification | cs.CV | We consider a pipeline for image classification or search based on coding
approaches like Bag of Words or Fisher vectors. In this context, the most
common approach is to extract the image patches regularly in a dense manner on
several scales. This paper proposes and evaluates alternative choices to
extract patches dens... | computer science |
24,706 | Symmetric low-rank representation for subspace clustering | cs.CV | We propose a symmetric low-rank representation (SLRR) method for subspace
clustering, which assumes that a data set is approximately drawn from the union
of multiple subspaces. The proposed technique can reveal the membership of
multiple subspaces through the self-expressiveness property of the data. In
particular, the... | computer science |
24,707 | Generalized Adaptive Dictionary Learning via Domain Shift Minimization | cs.CV | Visual data driven dictionaries have been successfully employed for various
object recognition and classification tasks. However, the task becomes more
challenging if the training and test data are from contrasting domains. In this
paper, we propose a novel and generalized approach towards learning an adaptive
and comm... | computer science |
24,708 | Complex Events Recognition under Uncertainty in a Sensor Network | cs.CV | Automated extraction of semantic information from a network of sensors for
cognitive analysis and human-like reasoning is a desired capability in future
ground surveillance systems. We tackle the problem of complex decision making
under uncertainty in network information environment, where lack of effective
visual proc... | computer science |
24,709 | Detection of texts in natural images | cs.CV | A framework that makes use of Connected components and supervised Support
machine to recognise texts is proposed. The image is preprocessed and and edge
graph is calculated using a probabilistic framework to compensate for
photometric noise. Connected components over the resultant image is calculated,
which is bounded ... | computer science |
24,710 | A Two-phase Decision Support Framework for the Automatic Screening of
Digital Fundus Images | cs.CV | In this paper we give a brief review on the present status of automated
detection systems describe for the screening of diabetic retinopathy. We
further detail an enhanced detection procedure that consists of two steps.
First, a pre-screening algorithm is considered to classify the input digital
fundus images based on ... | computer science |
24,711 | High Dynamic Range Imaging by Perceptual Logarithmic Exposure Merging | cs.CV | In this paper we emphasize a similarity between the Logarithmic-Type Image
Processing (LTIP) model and the Naka-Rushton model of the Human Visual System
(HVS). LTIP is a derivation of the Logarithmic Image Processing (LIP), which
further replaces the logarithmic function with a ratio of polynomial functions.
Based on t... | computer science |
24,712 | Sparsity Constrained Graph Regularized NMF for Spectral Unmixing of
Hyperspectral Data | cs.CV | Hyperspectral images contain mixed pixels due to low spatial resolution of
hyperspectral sensors. Mixed pixels are pixels containing more than one
distinct material called endmembers. The presence percentages of endmembers in
mixed pixels are called abundance fractions. Spectral unmixing problem refers
to decomposing t... | computer science |
24,713 | Non Binary Local Gradient Contours for Face Recognition | cs.CV | As the features from the traditional Local Binary Patterns (LBP) and Local
Directional Patterns (LDP) are found to be ineffective for face recognition, we
have proposed a new approach derived on the basis of Information sets whereby
the loss of information that occurs during the binarization is eliminated. The
informat... | computer science |
24,714 | Affective Facial Expression Processing via Simulation: A Probabilistic
Model | cs.CV | Understanding the mental state of other people is an important skill for
intelligent agents and robots to operate within social environments. However,
the mental processes involved in `mind-reading' are complex. One explanation of
such processes is Simulation Theory - it is supported by a large body of
neuropsychologic... | computer science |
24,715 | State-of-the-Art in Retinal Optical Coherence Tomography Image Analysis | cs.CV | Optical Coherence Tomography (OCT) is one of the most emerging imaging
modalities that has been used widely in the field of biomedical imaging. From
its emergence in 1990's, plenty of hardware and software improvements have been
made. Its applications range from ophthalmology to dermatology to coronary
imaging etc. Her... | computer science |
24,716 | A Robust Point Sets Matching Method | cs.CV | Point sets matching method is very important in computer vision, feature
extraction, fingerprint matching, motion estimation and so on. This paper
proposes a robust point sets matching method. We present an iterative algorithm
that is robust to noise case. Firstly, we calculate all transformations between
two points. T... | computer science |
24,717 | Multilinear Principal Component Analysis Network for Tensor Object
Classification | cs.CV | The recently proposed principal component analysis network (PCANet) has been
proved high performance for visual content classification. In this letter, we
develop a tensorial extension of PCANet, namely, multilinear principal analysis
component network (MPCANet), for tensor object classification. Compared to
PCANet, th... | computer science |
24,718 | Tensor object classification via multilinear discriminant analysis
network | cs.CV | This paper proposes a multilinear discriminant analysis network (MLDANet) for
the recognition of multidimensional objects, known as tensor objects. The
MLDANet is a variation of linear discriminant analysis network (LDANet) and
principal component analysis network (PCANet), both of which are the recently
proposed deep ... | computer science |
24,719 | Edge Detection based on Kernel Density Estimation | cs.CV | Edges of an image are considered a crucial type of information. These can be
extracted by applying edge detectors with different methodology. Edge detection
is a vital step in computer vision tasks, because it is an essential issue for
pattern recognition and visual interpretation. In this paper, we propose a new
metho... | computer science |
24,720 | Optical Character Recognition, Using K-Nearest Neighbors | cs.CV | The problem of optical character recognition, OCR, has been widely discussed
in the literature. Having a hand-written text, the program aims at recognizing
the text. Even though there are several approaches to this issue, it is still
an open problem. In this paper we would like to propose an approach that uses
K-neares... | computer science |
24,721 | Parallax Effect Free Mosaicing of Underwater Video Sequence Based on
Texture Features | cs.CV | In this paper, we present feature-based technique for construction of mosaic
image from underwater video sequence, which suffers from parallax distortion
due to propagation properties of light in the underwater environment. The most
of the available mosaic tools and underwater image mosaicing techniques yields
final re... | computer science |
24,722 | Fast Mesh-Based Medical Image Registration | cs.CV | In this paper a fast triangular mesh based registration method is proposed.
Having Template and Reference images as inputs, the template image is
triangulated using a content adaptive mesh generation algorithm. Considering
the pixel values at mesh nodes, interpolated using spline interpolation method
for both of the im... | computer science |
24,723 | Stacked Quantizers for Compositional Vector Compression | cs.CV | Recently, Babenko and Lempitsky introduced Additive Quantization (AQ), a
generalization of Product Quantization (PQ) where a non-independent set of
codebooks is used to compress vectors into small binary codes. Unfortunately,
under this scheme encoding cannot be done independently in each codebook, and
optimal encoding... | computer science |
24,724 | Abnormal Object Recognition: A Comprehensive Study | cs.CV | When describing images, humans tend not to talk about the obvious, but rather
mention what they find interesting. We argue that abnormalities and deviations
from typicalities are among the most important components that form what is
worth mentioning. In this paper we introduce the abnormality detection as a
recognition... | computer science |
24,725 | An Improved Tracking using IMU and Vision Fusion for Mobile Augmented
Reality Applications | cs.CV | Mobile Augmented Reality (MAR) is becoming an important cyber-physical system
application given the ubiquitous availability of mobile phones. With the need
to operate in unprepared environments, accurate and robust registration and
tracking has become an important research problem to solve. In fact, when MAR
is used fo... | computer science |
24,726 | Computational Baby Learning | cs.CV | Intuitive observations show that a baby may inherently possess the capability
of recognizing a new visual concept (e.g., chair, dog) by learning from only
very few positive instances taught by parent(s) or others, and this recognition
capability can be gradually further improved by exploring and/or interacting
with the... | computer science |
24,727 | 3D Shape Estimation from 2D Landmarks: A Convex Relaxation Approach | cs.CV | We investigate the problem of estimating the 3D shape of an object, given a
set of 2D landmarks in a single image. To alleviate the reconstruction
ambiguity, a widely-used approach is to confine the unknown 3D shape within a
shape space built upon existing shapes. While this approach has proven to be
successful in vari... | computer science |
24,728 | Collecting Image Description Datasets using Crowdsourcing | cs.CV | We describe our two new datasets with images described by humans. Both the
datasets were collected using Amazon Mechanical Turk, a crowdsourcing platform.
The two datasets contain significantly more descriptions per image than other
existing datasets. One is based on a popular image description dataset called
the UIUC ... | computer science |
24,729 | Part Detector Discovery in Deep Convolutional Neural Networks | cs.CV | Current fine-grained classification approaches often rely on a robust
localization of object parts to extract localized feature representations
suitable for discrimination. However, part localization is a challenging task
due to the large variation of appearance and pose. In this paper, we show how
pre-trained convolut... | computer science |
24,730 | Multi-modal Image Registration for Correlative Microscopy | cs.CV | Correlative microscopy is a methodology combining the functionality of light
microscopy with the high resolution of electron microscopy and other microscopy
technologies. Image registration for correlative microscopy is quite
challenging because it is a multi-modal, multi-scale and multi-dimensional
registration proble... | computer science |
24,731 | Sparse Modeling for Image and Vision Processing | cs.CV | In recent years, a large amount of multi-disciplinary research has been
conducted on sparse models and their applications. In statistics and machine
learning, the sparsity principle is used to perform model selection---that is,
automatically selecting a simple model among a large collection of them. In
signal processin... | computer science |
24,732 | Amoeba Techniques for Shape and Texture Analysis | cs.CV | Morphological amoebas are image-adaptive structuring elements for
morphological and other local image filters introduced by Lerallut et al. Their
construction is based on combining spatial distance with contrast information
into an image-dependent metric. Amoeba filters show interesting parallels to
image filtering met... | computer science |
24,733 | Person Re-identification Based on Color Histogram and Spatial
Configuration of Dominant Color Regions | cs.CV | There is a requirement to determine whether a given person of interest has
already been observed over a network of cameras in video surveillance systems.
A human appearance obtained in one camera is usually different from the ones
obtained in another camera due to difference in illumination, pose and
viewpoint, camera ... | computer science |
24,734 | A Comparative Study of Techniques of Distant Reconstruction of
Displacement Fields by using DISTRESS Simulator | cs.CV | Reconstruction and monitoring of displacement and strain fields is an
important problem in engineering. We analyze the remote and non-obtrusive
methods of strain measurement based on photogrammetry and Digital Image
Correlation (DIC). The method is based on covering the photographed surface
with a pattern of speckles a... | computer science |
24,735 | Window-Based Descriptors for Arabic Handwritten Alphabet Recognition: A
Comparative Study on a Novel Dataset | cs.CV | This paper presents a comparative study for window-based descriptors on the
application of Arabic handwritten alphabet recognition. We show a detailed
experimental evaluation of different descriptors with several classifiers. The
objective of the paper is to evaluate different window-based descriptors on the
problem of... | computer science |
24,736 | A Discriminative CNN Video Representation for Event Detection | cs.CV | In this paper, we propose a discriminative video representation for event
detection over a large scale video dataset when only limited hardware resources
are available. The focus of this paper is to effectively leverage deep
Convolutional Neural Networks (CNNs) to advance event detection, where only
frame level static ... | computer science |
24,737 | Sparse And Low Rank Decomposition Based Batch Image Alignment for
Speckle Reduction of retinal OCT Images | cs.CV | Optical Coherence Tomography (OCT) is an emerging technique in the field of
biomedical imaging, with applications in ophthalmology, dermatology, coronary
imaging etc. Due to the underlying physics, OCT images usually suffer from a
granular pattern, called speckle noise, which restricts the process of
interpretation. He... | computer science |
24,738 | Fully Convolutional Networks for Semantic Segmentation | cs.CV | Convolutional networks are powerful visual models that yield hierarchies of
features. We show that convolutional networks by themselves, trained
end-to-end, pixels-to-pixels, exceed the state-of-the-art in semantic
segmentation. Our key insight is to build "fully convolutional" networks that
take input of arbitrary siz... | computer science |
24,739 | A Faster Method for Tracking and Scoring Videos Corresponding to
Sentences | cs.CV | Prior work presented the sentence tracker, a method for scoring how well a
sentence describes a video clip or alternatively how well a video clip depicts
a sentence. We present an improved method for optimizing the same cost function
employed by this prior work, reducing the space complexity from exponential in
the sen... | computer science |
24,740 | Efficient and Accurate Approximations of Nonlinear Convolutional
Networks | cs.CV | This paper aims to accelerate the test-time computation of deep convolutional
neural networks (CNNs). Unlike existing methods that are designed for
approximating linear filters or linear responses, our method takes the
nonlinear units into account. We minimize the reconstruction error of the
nonlinear responses, subjec... | computer science |
24,741 | Efficient Object Localization Using Convolutional Networks | cs.CV | Recent state-of-the-art performance on human-body pose estimation has been
achieved with Deep Convolutional Networks (ConvNets). Traditional ConvNet
architectures include pooling and sub-sampling layers which reduce
computational requirements, introduce invariance and prevent over-training.
These benefits of pooling co... | computer science |
24,742 | Combining contextual and local edges for line segment extraction in
cluttered images | cs.CV | Automatic extraction methods typically assume that line segments are
pronounced, thin, few and far between, do not cross each other, and are noise
and clutter-free. Since these assumptions often fail in realistic scenarios,
many line segments are not detected or are fragmented. In more severe cases,
i.e., many who use ... | computer science |
24,743 | Ten Years of Pedestrian Detection, What Have We Learned? | cs.CV | Paper-by-paper results make it easy to miss the forest for the trees.We
analyse the remarkable progress of the last decade by discussing the main ideas
explored in the 40+ detectors currently present in the Caltech pedestrian
detection benchmark. We observe that there exist three families of approaches,
all currently r... | computer science |
24,744 | A Latent Clothing Attribute Approach for Human Pose Estimation | cs.CV | As a fundamental technique that concerns several vision tasks such as image
parsing, action recognition and clothing retrieval, human pose estimation (HPE)
has been extensively investigated in recent years. To achieve accurate and
reliable estimation of the human pose, it is well-recognized that the clothing
attributes... | computer science |
24,745 | Long-term Recurrent Convolutional Networks for Visual Recognition and
Description | cs.CV | Models based on deep convolutional networks have dominated recent image
interpretation tasks; we investigate whether models which are also recurrent,
or "temporally deep", are effective for tasks involving sequences, visual and
otherwise. We develop a novel recurrent convolutional architecture suitable for
large-scale ... | computer science |
24,746 | Automatic Subspace Learning via Principal Coefficients Embedding | cs.CV | In this paper, we address two challenging problems in unsupervised subspace
learning: 1) how to automatically identify the feature dimension of the learned
subspace (i.e., automatic subspace learning), and 2) how to learn the
underlying subspace in the presence of Gaussian noise (i.e., robust subspace
learning). We sho... | computer science |
24,747 | A Nonparametric Bayesian Approach Toward Stacked Convolutional
Independent Component Analysis | cs.CV | Unsupervised feature learning algorithms based on convolutional formulations
of independent components analysis (ICA) have been demonstrated to yield
state-of-the-art results in several action recognition benchmarks. However,
existing approaches do not allow for the number of latent components (features)
to be automati... | computer science |
24,748 | Fully Convolutional Neural Networks for Crowd Segmentation | cs.CV | In this paper, we propose a fast fully convolutional neural network (FCNN)
for crowd segmentation. By replacing the fully connected layers in CNN with 1
by 1 convolution kernels, FCNN takes whole images as inputs and directly
outputs segmentation maps by one pass of forward propagation. It has the
property of translati... | computer science |
24,749 | Show and Tell: A Neural Image Caption Generator | cs.CV | Automatically describing the content of an image is a fundamental problem in
artificial intelligence that connects computer vision and natural language
processing. In this paper, we present a generative model based on a deep
recurrent architecture that combines recent advances in computer vision and
machine translation... | computer science |
24,750 | TILDE: A Temporally Invariant Learned DEtector | cs.CV | We introduce a learning-based approach to detect repeatable keypoints under
drastic imaging changes of weather and lighting conditions to which
state-of-the-art keypoint detectors are surprisingly sensitive. We first
identify good keypoint candidates in multiple training images taken from the
same viewpoint. We then tr... | computer science |
24,751 | AlexU-Word: A New Dataset for Isolated-Word Closed-Vocabulary Offline
Arabic Handwriting Recognition | cs.CV | In this paper, we introduce the first phase of a new dataset for offline
Arabic handwriting recognition. The aim is to collect a very large dataset of
isolated Arabic words that covers all letters of the alphabet in all possible
shapes using a small number of simple words. The end goal is to collect a very
large datase... | computer science |
24,752 | Predicting Depth, Surface Normals and Semantic Labels with a Common
Multi-Scale Convolutional Architecture | cs.CV | In this paper we address three different computer vision tasks using a single
basic architecture: depth prediction, surface normal estimation, and semantic
labeling. We use a multiscale convolutional network that is able to adapt
easily to each task using only small modifications, regressing from the input
image to the... | computer science |
24,753 | Low-level Vision by Consensus in a Spatial Hierarchy of Regions | cs.CV | We introduce a multi-scale framework for low-level vision, where the goal is
estimating physical scene values from image data---such as depth from stereo
image pairs. The framework uses a dense, overlapping set of image regions at
multiple scales and a "local model," such as a slanted-plane model for stereo
disparity, ... | computer science |
24,754 | Designing Deep Networks for Surface Normal Estimation | cs.CV | In the past few years, convolutional neural nets (CNN) have shown incredible
promise for learning visual representations. In this paper, we use CNNs for the
task of predicting surface normals from a single image. But what is the right
architecture we should use? We propose to build upon the decades of hard work
in 3D s... | computer science |
24,755 | Fast Iteratively Reweighted Least Squares Algorithms for Analysis-Based
Sparsity Reconstruction | cs.CV | In this paper, we propose a novel algorithm for analysis-based sparsity
reconstruction. It can solve the generalized problem by structured sparsity
regularization with an orthogonal basis and total variation regularization. The
proposed algorithm is based on the iterative reweighted least squares (IRLS)
model, which is... | computer science |
24,756 | SIRF: Simultaneous Image Registration and Fusion in A Unified Framework | cs.CV | In this paper, we propose a novel method for image fusion with a
high-resolution panchromatic image and a low-resolution multispectral image at
the same geographical location. The fusion is formulated as a convex
optimization problem which minimizes a linear combination of a least-squares
fitting term and a dynamic gra... | computer science |
24,757 | A Pooling Approach to Modelling Spatial Relations for Image Retrieval
and Annotation | cs.CV | Over the last two decades we have witnessed strong progress on modeling
visual object classes, scenes and attributes that have significantly
contributed to automated image understanding. On the other hand, surprisingly
little progress has been made on incorporating a spatial representation and
reasoning in the inferenc... | computer science |
24,758 | End-to-End Integration of a Convolutional Network, Deformable Parts
Model and Non-Maximum Suppression | cs.CV | Deformable Parts Models and Convolutional Networks each have achieved notable
performance in object detection. Yet these two approaches find their strengths
in complementary areas: DPMs are well-versed in object composition, modeling
fine-grained spatial relationships between parts; likewise, ConvNets are adept
at prod... | computer science |
24,759 | Fashion Apparel Detection: The Role of Deep Convolutional Neural Network
and Pose-dependent Priors | cs.CV | In this work, we propose and address a new computer vision task, which we
call fashion item detection, where the aim is to detect various fashion items a
person in the image is wearing or carrying. The types of fashion items we
consider in this work include hat, glasses, bag, pants, shoes and so on. The
detection of fa... | computer science |
24,760 | Maximum Likelihood Directed Enumeration Method in Piecewise-Regular
Object Recognition | cs.CV | We explore the problems of classification of composite object (images, speech
signals) with low number of models per class. We study the question of
improving recognition performance for medium-sized database (thousands of
classes). The key issue of fast approximate nearest-neighbor methods widely
applied in this task ... | computer science |
24,761 | Hypercolumns for Object Segmentation and Fine-grained Localization | cs.CV | Recognition algorithms based on convolutional networks (CNNs) typically use
the output of the last layer as feature representation. However, the
information in this layer may be too coarse to allow precise localization. On
the contrary, earlier layers may be precise in localization but will not
capture semantics. To ge... | computer science |
24,762 | Assessment of algorithms for mitosis detection in breast cancer
histopathology images | cs.CV | The proliferative activity of breast tumors, which is routinely estimated by
counting of mitotic figures in hematoxylin and eosin stained histology
sections, is considered to be one of the most important prognostic markers.
However, mitosis counting is laborious, subjective and may suffer from low
inter-observer agreem... | computer science |
24,763 | A Unified Semantic Embedding: Relating Taxonomies and Attributes | cs.CV | We propose a method that learns a discriminative yet semantic space for
object categorization, where we also embed auxiliary semantic entities such as
supercategories and attributes. Contrary to prior work which only utilized them
as side information, we explicitly embed the semantic entities into the same
space where ... | computer science |
24,764 | Towards Scene Understanding with Detailed 3D Object Representations | cs.CV | Current approaches to semantic image and scene understanding typically employ
rather simple object representations such as 2D or 3D bounding boxes. While
such coarse models are robust and allow for reliable object detection, they
discard much of the information about objects' 3D shape and pose, and thus do
not lend the... | computer science |
24,765 | Finding Action Tubes | cs.CV | We address the problem of action detection in videos. Driven by the latest
progress in object detection from 2D images, we build action models using rich
feature hierarchies derived from shape and kinematic cues. We incorporate
appearance and motion in two ways. First, starting from image region proposals
we select tho... | computer science |
24,766 | Viewpoints and Keypoints | cs.CV | We characterize the problem of pose estimation for rigid objects in terms of
determining viewpoint to explain coarse pose and keypoint prediction to capture
the finer details. We address both these tasks in two different settings - the
constrained setting with known bounding boxes and the more challenging
detection set... | computer science |
24,767 | Category-Specific Object Reconstruction from a Single Image | cs.CV | Object reconstruction from a single image -- in the wild -- is a problem
where we can make progress and get meaningful results today. This is the main
message of this paper, which introduces an automated pipeline with pixels as
inputs and 3D surfaces of various rigid categories as outputs in images of
realistic scenes.... | computer science |
24,768 | Virtual View Networks for Object Reconstruction | cs.CV | All that structure from motion algorithms "see" are sets of 2D points. We
show that these impoverished views of the world can be faked for the purpose of
reconstructing objects in challenging settings, such as from a single image, or
from a few ones far apart, by recognizing the object and getting help from a
collectio... | computer science |
24,769 | Low-Rank and Sparse Matrix Decomposition with a-priori knowledge for
Dynamic 3D MRI reconstruction | cs.CV | It has been recently shown that incorporating priori knowledge significantly
improves the performance of basic compressive sensing based approaches. We have
managed to successfully exploit this idea for recovering a matrix as a
summation of a Low-rank and a Sparse component from compressive measurements.
When applied t... | computer science |
24,770 | From Image-level to Pixel-level Labeling with Convolutional Networks | cs.CV | We are interested in inferring object segmentation by leveraging only object
class information, and by considering only minimal priors on the object
segmentation task. This problem could be viewed as a kind of weakly supervised
segmentation task, and naturally fits the Multiple Instance Learning (MIL)
framework: every ... | computer science |
24,771 | Detection of Non-Stationary Photometric Perturbations on Projection
Screens | cs.CV | Interfaces based on projection screens have become increasingly more popular
in recent years, mainly due to the large screen size and resolution that they
provide, as well as their stereo-vision capabilities. This work shows a local
method for real-time detection of non-stationary photometric perturbations in
projected... | computer science |
24,772 | Iteratively Reweighted Graph Cut for Multi-label MRFs with Non-convex
Priors | cs.CV | While widely acknowledged as highly effective in computer vision, multi-label
MRFs with non-convex priors are difficult to optimize. To tackle this, we
introduce an algorithm that iteratively approximates the original energy with
an appropriately weighted surrogate energy that is easier to minimize. Our
algorithm guara... | computer science |
24,773 | On the mathematic modeling of non-parametric curves based on cubic
Bézier curves | cs.CV | B\'ezier splines are widely available in various systems with the curves and
surface designs. In general, the B\'ezier spline can be specified with the
B\'ezier curve segments and a B\'ezier curve segment can be fitted to any
number of control points. The number of control points determines the degree of
the B\'ezier p... | computer science |
24,774 | Mid-level Deep Pattern Mining | cs.CV | Mid-level visual element discovery aims to find clusters of image patches
that are both representative and discriminative. In this work, we study this
problem from the prospective of pattern mining while relying on the recently
popularized Convolutional Neural Networks (CNNs). Specifically, we find that
for an image pa... | computer science |
24,775 | Deep Convolutional Neural Fields for Depth Estimation from a Single
Image | cs.CV | We consider the problem of depth estimation from a single monocular image in
this work. It is a challenging task as no reliable depth cues are available,
e.g., stereo correspondences, motions, etc. Previous efforts have been focusing
on exploiting geometric priors or additional sources of information, with all
using ha... | computer science |
24,776 | Encoding High Dimensional Local Features by Sparse Coding Based Fisher
Vectors | cs.CV | Deriving from the gradient vector of a generative model of local features,
Fisher vector coding (FVC) has been identified as an effective coding method
for image classification. Most, if not all, % FVC implementations employ the
Gaussian mixture model (GMM) to characterize the generation process of local
features. This... | computer science |
24,777 | The Application of Two-level Attention Models in Deep Convolutional
Neural Network for Fine-grained Image Classification | cs.CV | Fine-grained classification is challenging because categories can only be
discriminated by subtle and local differences. Variances in the pose, scale or
rotation usually make the problem more difficult. Most fine-grained
classification systems follow the pipeline of finding foreground object or
object parts (where) to ... | computer science |
24,778 | Persistent Evidence of Local Image Properties in Generic ConvNets | cs.CV | Supervised training of a convolutional network for object classification
should make explicit any information related to the class of objects and
disregard any auxiliary information associated with the capture of the image or
the variation within the object class. Does this happen in practice? Although
this seems to pe... | computer science |
24,779 | Beyond Gaussian Pyramid: Multi-skip Feature Stacking for Action
Recognition | cs.CV | Most state-of-the-art action feature extractors involve differential
operators, which act as highpass filters and tend to attenuate low frequency
action information. This attenuation introduces bias to the resulting features
and generates ill-conditioned feature matrices. The Gaussian Pyramid has been
used as a feature... | computer science |
24,780 | Deep convolutional filter banks for texture recognition and segmentation | cs.CV | Research in texture recognition often concentrates on the problem of material
recognition in uncluttered conditions, an assumption rarely met by
applications. In this work we conduct a first study of material and describable
texture at- tributes recognition in clutter, using a new dataset derived from
the OpenSurface t... | computer science |
24,781 | Similarity- based approach for outlier detection | cs.CV | This paper presents a new approach for detecting outliers by introducing the
notion of object's proximity. The main idea is that normal point has similar
characteristics with several neighbors. So the point in not an outlier if it
has a high degree of proximity and its neighbors are several. The performance
of this app... | computer science |
24,782 | Image Classification and Retrieval from User-Supplied Tags | cs.CV | This paper proposes direct learning of image classification from
user-supplied tags, without filtering. Each tag is supplied by the user who
shared the image online. Enormous numbers of these tags are freely available
online, and they give insight about the image categories important to users and
to image classificatio... | computer science |
24,783 | Fisher Vectors Derived from Hybrid Gaussian-Laplacian Mixture Models for
Image Annotation | cs.CV | In the traditional object recognition pipeline, descriptors are densely
sampled over an image, pooled into a high dimensional non-linear representation
and then passed to a classifier. In recent years, Fisher Vectors have proven
empirically to be the leading representation for a large variety of
applications. The Fishe... | computer science |
24,784 | The Treasure beneath Convolutional Layers: Cross-convolutional-layer
Pooling for Image Classification | cs.CV | A number of recent studies have shown that a Deep Convolutional Neural
Network (DCNN) pretrained on a large dataset can be adopted as a universal
image description which leads to astounding performance in many visual
classification tasks. Most of these studies, if not all, adopt activations of
the fully-connected layer... | computer science |
24,785 | Large-scale Binary Quadratic Optimization Using Semidefinite Relaxation
and Applications | cs.CV | In computer vision, many problems such as image segmentation, pixel
labelling, and scene parsing can be formulated as binary quadratic programs
(BQPs). For submodular problems, cuts based methods can be employed to
efficiently solve large-scale problems. However, general nonsubmodular problems
are significantly more ch... | computer science |
24,786 | An Egocentric Look at Video Photographer Identity | cs.CV | Egocentric cameras are being worn by an increasing number of users, among
them many security forces worldwide. GoPro cameras already penetrated the mass
market, reporting substantial increase in sales every year. As head-worn
cameras do not capture the photographer, it may seem that the anonymity of the
photographer is... | computer science |
24,787 | A statistical reduced-reference method for color image quality
assessment | cs.CV | Although color is a fundamental feature of human visual perception, it has
been largely unexplored in the reduced-reference (RR) image quality assessment
(IQA) schemes. In this paper, we propose a natural scene statistic (NSS)
method, which efficiently uses this information. It is based on the statistical
deviation bet... | computer science |
24,788 | Visual Representations: Defining Properties and Deep Approximations | cs.CV | Visual representations are defined in terms of minimal sufficient statistics
of visual data, for a class of tasks, that are also invariant to nuisance
variability. Minimal sufficiency guarantees that we can store a representation
in lieu of raw data with smallest complexity and no performance loss on the
task at hand. ... | computer science |
24,789 | On color image quality assessment using natural image statistics | cs.CV | Color distortion can introduce a significant damage in visual quality
perception, however, most of existing reduced-reference quality measures are
designed for grayscale images. In this paper, we consider a basic extension of
well-known image-statistics based quality assessment measures to color images.
In order to eva... | computer science |
24,790 | Features in Concert: Discriminative Feature Selection meets Unsupervised
Clustering | cs.CV | Feature selection is an essential problem in computer vision, important for
category learning and recognition. Along with the rapid development of a wide
variety of visual features and classifiers, there is a growing need for
efficient feature selection and combination methods, to construct powerful
classifiers for mor... | computer science |
24,791 | Flying Objects Detection from a Single Moving Camera | cs.CV | We propose an approach to detect flying objects such as UAVs and aircrafts
when they occupy a small portion of the field of view, possibly moving against
complex backgrounds, and are filmed by a camera that itself moves.
Solving such a difficult problem requires combining both appearance and
motion cues. To this end ... | computer science |
24,792 | Deep Learning Face Attributes in the Wild | cs.CV | Predicting face attributes in the wild is challenging due to complex face
variations. We propose a novel deep learning framework for attribute prediction
in the wild. It cascades two CNNs, LNet and ANet, which are fine-tuned jointly
with attribute tags, but pre-trained differently. LNet is pre-trained by
massive genera... | computer science |
24,793 | Cross-Modal Learning via Pairwise Constraints | cs.CV | In multimedia applications, the text and image components in a web document
form a pairwise constraint that potentially indicates the same semantic
concept. This paper studies cross-modal learning via the pairwise constraint,
and aims to find the common structure hidden in different modalities. We first
propose a compo... | computer science |
24,794 | V-variable image compression | cs.CV | V-variable fractals, where $V$ is a positive integer, are intuitively
fractals with at most $V$ different "forms" or "shapes" at all levels of
magnification. In this paper we describe how V-variable fractals can be used
for the purpose of image compression. | computer science |
24,795 | Articulated motion discovery using pairs of trajectories | cs.CV | We propose an unsupervised approach for discovering characteristic motion
patterns in videos of highly articulated objects performing natural, unscripted
behaviors, such as tigers in the wild. We discover consistent patterns in a
bottom-up manner by analyzing the relative displacements of large numbers of
ordered traje... | computer science |
24,796 | On Rendering Synthetic Images for Training an Object Detector | cs.CV | We propose a novel approach to synthesizing images that are effective for
training object detectors. Starting from a small set of real images, our
algorithm estimates the rendering parameters required to synthesize similar
images given a coarse 3D model of the target object. These parameters can then
be reused to gener... | computer science |
24,797 | Learning Face Representation from Scratch | cs.CV | Pushing by big data and deep convolutional neural network (CNN), the
performance of face recognition is becoming comparable to human. Using private
large scale training datasets, several groups achieve very high performance on
LFW, i.e., 97% to 99%. While there are many open source implementations of CNN,
none of large... | computer science |
24,798 | Multiple object tracking with context awareness | cs.CV | Multiple people tracking is a key problem for many applications such as
surveillance, animation or car navigation, and a key input for tasks such as
activity recognition. In crowded environments occlusions and false detections
are common, and although there have been substantial advances in recent years,
tracking is st... | computer science |
24,799 | Effective Face Frontalization in Unconstrained Images | cs.CV | "Frontalization" is the process of synthesizing frontal facing views of faces
appearing in single unconstrained photos. Recent reports have suggested that
this process may substantially boost the performance of face recognition
systems. This, by transforming the challenging problem of recognizing faces
viewed from unco... | computer science |
24,800 | 3D-Assisted Image Feature Synthesis for Novel Views of an Object | cs.CV | Comparing two images in a view-invariant way has been a challenging problem
in computer vision for a long time, as visual features are not stable under
large view point changes. In this paper, given a single input image of an
object, we synthesize new features for other views of the same object. To
accomplish this, we ... | computer science |
24,801 | Understanding Deep Image Representations by Inverting Them | cs.CV | Image representations, from SIFT and Bag of Visual Words to Convolutional
Neural Networks (CNNs), are a crucial component of almost any image
understanding system. Nevertheless, our understanding of them remains limited.
In this paper we conduct a direct analysis of the visual information contained
in representations b... | computer science |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.