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25,402 | Using User Generated Online Photos to Estimate and Monitor Air Pollution
in Major Cities | cs.CV | With the rapid development of economy in China over the past decade, air
pollution has become an increasingly serious problem in major cities and caused
grave public health concerns in China. Recently, a number of studies have dealt
with air quality and air pollution. Among them, some attempt to predict and
monitor the... | computer science |
25,403 | Seeing Behind the Camera: Identifying the Authorship of a Photograph | cs.CV | We introduce the novel problem of identifying the photographer behind a
photograph. To explore the feasibility of current computer vision techniques to
address this problem, we created a new dataset of over 180,000 images taken by
41 well-known photographers. Using this dataset, we examined the effectiveness
of a varie... | computer science |
25,404 | Improving Image Restoration with Soft-Rounding | cs.CV | Several important classes of images such as text, barcode and pattern images
have the property that pixels can only take a distinct subset of values. This
knowledge can benefit the restoration of such images, but it has not been
widely considered in current restoration methods. In this work, we describe an
effective an... | computer science |
25,405 | Flow Fields: Dense Correspondence Fields for Highly Accurate Large
Displacement Optical Flow Estimation | cs.CV | Modern large displacement optical flow algorithms usually use an
initialization by either sparse descriptor matching techniques or dense
approximate nearest neighbor fields. While the latter have the advantage of
being dense, they have the major disadvantage of being very outlier prone as
they are not designed to find ... | computer science |
25,406 | Exemplar Based Deep Discriminative and Shareable Feature Learning for
Scene Image Classification | cs.CV | In order to encode the class correlation and class specific information in
image representation, we propose a new local feature learning approach named
Deep Discriminative and Shareable Feature Learning (DDSFL). DDSFL aims to
hierarchically learn feature transformation filter banks to transform raw pixel
image patches ... | computer science |
25,407 | Morphometry-Based Longitudinal Neurodegeneration Simulation with MR
Imaging | cs.CV | We present a longitudinal MR simulation framework which simulates the future
neurodegenerative progression by outputting the predicted follow-up MR image
and the voxel-based morphometry (VBM) map. This framework expects the patients
to have at least 2 historical MR images available. The longitudinal and
cross-sectional... | computer science |
25,408 | Iterative Thresholded Bi-Histogram Equalization for Medical Image
Enhancement | cs.CV | Enhancement of human vision to get an insight to information content is of
vital importance. The traditional histogram equalization methods have been
suffering from amplified contrast with the addition of artifacts and a
surprising unnatural visibility of the processed images. In order to overcome
these drawbacks, this... | computer science |
25,409 | Optical images-based edge detection in Synthetic Aperture Radar images | cs.CV | We address the issue of adapting optical images-based edge detection
techniques for use in Polarimetric Synthetic Aperture Radar (PolSAR) imagery.
We modify the gravitational edge detection technique (inspired by the Law of
Universal Gravity) proposed by Lopez-Molina et al, using the non-standard
neighbourhood configur... | computer science |
25,410 | An algorithm for Left Atrial Thrombi detection using Transesophageal
Echocardiography | cs.CV | Transesophageal echocardiography (TEE) is widely used to detect left atrium
(LA)/left atrial appendage (LAA) thrombi. In this paper, the local binary
pattern variance (LBPV) features are extracted from region of interest (ROI).
And the dynamic features are formed by using the information of its neighbor
frames in the s... | computer science |
25,411 | Wavelet subspace decomposition of thermal infrared images for defect
detection in artworks | cs.CV | Monitoring the health of ancient artworks requires adequate prudence because
of the sensitive nature of these materials. Classical techniques for
identifying the development of faults rely on acoustic testing. These
techniques, being invasive, may result in causing permanent damage to the
material, especially if the ma... | computer science |
25,412 | Cooking in the kitchen: Recognizing and Segmenting Human Activities in
Videos | cs.CV | As research on action recognition matures, the focus is shifting away from
categorizing basic task-oriented actions using hand-segmented video datasets to
understanding complex goal-oriented daily human activities in real-world
settings. Temporally structured models would seem obvious to tackle this set of
problems, bu... | computer science |
25,413 | Accurate Urban Road Centerline Extraction from VHR Imagery via
Multiscale Segmentation and Tensor Voting | cs.CV | It is very useful and increasingly popular to extract accurate road
centerlines from very-high-resolution (VHR) re- mote sensing imagery for
various applications, such as road map generation and updating etc. There are
three shortcomings of current methods: (a) Due to the noise and occlusions
(owing to vehicles and tre... | computer science |
25,414 | SPF-CellTracker: Tracking multiple cells with strongly-correlated moves
using a spatial particle filter | cs.CV | Tracking many cells in time-lapse 3D image sequences is an important
challenging task of bioimage informatics. Motivated by a study of brain-wide 4D
imaging of neural activity in C. elegans, we present a new method of multi-cell
tracking. Data types to which the method is applicable are characterized as
follows: (i) ce... | computer science |
25,415 | Maximum-Margin Structured Learning with Deep Networks for 3D Human Pose
Estimation | cs.CV | This paper focuses on structured-output learning using deep neural networks
for 3D human pose estimation from monocular images. Our network takes an image
and 3D pose as inputs and outputs a score value, which is high when the
image-pose pair matches and low otherwise. The network structure consists of a
convolutional ... | computer science |
25,416 | Image Type Water Meter Character Recognition Based on Embedded DSP | cs.CV | In the paper, we combined DSP processor with image processing algorithm and
studied the method of water meter character recognition. We collected water
meter image through camera at a fixed angle, and the projection method is used
to recognize those digital images. The experiment results show that the method
can recogn... | computer science |
25,417 | A Comparative Analysis of Retrieval Techniques In Content Based Image
Retrieval | cs.CV | Basic group of visual techniques such as color, shape, texture are used in
Content Based Image Retrievals (CBIR) to retrieve query image or subregion of
image to find similar images in image database. To improve query result,
relevance feedback is used many times in CBIR to help user to express their
preference and imp... | computer science |
25,418 | Shopper Analytics: a customer activity recognition system using a
distributed RGB-D camera network | cs.CV | The aim of this paper is to present an integrated system consisted of a RGB-D
camera and a software able to monitor shoppers in intelligent retail
environments. We propose an innovative low cost smart system that can
understand the shoppers' behavior and, in particular, their interactions with
the products in the shelv... | computer science |
25,419 | Discrete Hashing with Deep Neural Network | cs.CV | This paper addresses the problem of learning binary hash codes for large
scale image search by proposing a novel hashing method based on deep neural
network. The advantage of our deep model over previous deep model used in
hashing is that our model contains necessary criteria for producing good codes
such as similarity... | computer science |
25,420 | Mixed Gaussian-Impulse Noise Removal from Highly Corrupted Images via
Adaptive Local and Nonlocal Statistical Priors | cs.CV | The motivation of this paper is to introduce a novel framework for the
restoration of images corrupted by mixed Gaussian-impulse noise. To this aim,
first, an adaptive curvelet thresholding criterion is proposed which tries to
adaptively remove the perturbations appeared during denoising process. Then, a
new statistica... | computer science |
25,421 | Image Annotation Incorporating Low-Rankness, Tag and Visual Correlation
and Inhomogeneous Errors | cs.CV | Tag-based image retrieval (TBIR) has drawn much attention in recent years due
to the explosive amount of digital images and crowdsourcing tags. However, TBIR
is still suffering from the incomplete and inaccurate tags provided by users,
posing a great challenge for tag-based image management applications. In this
work, ... | computer science |
25,422 | Love Thy Neighbors: Image Annotation by Exploiting Image Metadata | cs.CV | Some images that are difficult to recognize on their own may become more
clear in the context of a neighborhood of related images with similar
social-network metadata. We build on this intuition to improve multilabel image
annotation. Our model uses image metadata nonparametrically to generate
neighborhoods of related ... | computer science |
25,423 | Action Recognition by Hierarchical Mid-level Action Elements | cs.CV | Realistic videos of human actions exhibit rich spatiotemporal structures at
multiple levels of granularity: an action can always be decomposed into
multiple finer-grained elements in both space and time. To capture this
intuition, we propose to represent videos by a hierarchy of mid-level action
elements (MAEs), where ... | computer science |
25,424 | Approximate Nearest Neighbor Fields in Video | cs.CV | We introduce RIANN (Ring Intersection Approximate Nearest Neighbor search),
an algorithm for matching patches of a video to a set of reference patches in
real-time. For each query, RIANN finds potential matches by intersecting rings
around key points in appearance space. Its search complexity is reversely
correlated to... | computer science |
25,425 | FlatCam: Thin, Bare-Sensor Cameras using Coded Aperture and Computation | cs.CV | FlatCam is a thin form-factor lensless camera that consists of a coded mask
placed on top of a bare, conventional sensor array. Unlike a traditional,
lens-based camera where an image of the scene is directly recorded on the
sensor pixels, each pixel in FlatCam records a linear combination of light from
multiple scene e... | computer science |
25,426 | Discovery Radiomics for Pathologically-Proven Computed Tomography Lung
Cancer Prediction | cs.CV | Lung cancer is the leading cause for cancer related deaths. As such, there is
an urgent need for a streamlined process that can allow radiologists to provide
diagnosis with greater efficiency and accuracy. A powerful tool to do this is
radiomics: a high-dimension imaging feature set. In this study, we take the
idea of ... | computer science |
25,427 | Robust Face Recognition via Multimodal Deep Face Representation | cs.CV | Face images appeared in multimedia applications, e.g., social networks and
digital entertainment, usually exhibit dramatic pose, illumination, and
expression variations, resulting in considerable performance degradation for
traditional face recognition algorithms. This paper proposes a comprehensive
deep learning frame... | computer science |
25,428 | Fast Randomized Singular Value Thresholding for Low-rank Optimization | cs.CV | Rank minimization can be converted into tractable surrogate problems, such as
Nuclear Norm Minimization (NNM) and Weighted NNM (WNNM). The problems related
to NNM, or WNNM, can be solved iteratively by applying a closed-form proximal
operator, called Singular Value Thresholding (SVT), or Weighted SVT, but they
suffer f... | computer science |
25,429 | Iterative hypothesis testing for multi-object tracking in presence of
features with variable reliability | cs.CV | This paper assumes prior detections of multiple targets at each time instant,
and uses a graph-based approach to connect those detections across time, based
on their position and appearance estimates. In contrast to most earlier works
in the field, our framework has been designed to exploit the appearance
features, eve... | computer science |
25,430 | DAG-Recurrent Neural Networks For Scene Labeling | cs.CV | In image labeling, local representations for image units are usually
generated from their surrounding image patches, thus long-range contextual
information is not effectively encoded. In this paper, we introduce recurrent
neural networks (RNNs) to address this issue. Specifically, directed acyclic
graph RNNs (DAG-RNNs)... | computer science |
25,431 | Exploring Online Ad Images Using a Deep Convolutional Neural Network
Approach | cs.CV | Online advertising is a huge, rapidly growing advertising market in today's
world. One common form of online advertising is using image ads. A decision is
made (often in real time) every time a user sees an ad, and the advertiser is
eager to determine the best ad to display. Consequently, many algorithms have
been deve... | computer science |
25,432 | Manipulated Object Proposal: A Discriminative Object Extraction and
Feature Fusion Framework for First-Person Daily Activity Recognition | cs.CV | Detecting and recognizing objects interacting with humans lie in the center
of first-person (egocentric) daily activity recognition. However, due to noisy
camera motion and frequent changes in viewpoint and scale, most of the previous
egocentric action recognition methods fail to capture and model highly
discriminative... | computer science |
25,433 | Dictionary based Approach to Edge Detection | cs.CV | Edge detection is a very essential part of image processing, as quality and
accuracy of detection determines the success of further processing. We have
developed a new self learning technique for edge detection using dictionary
comprised of eigenfilters constructed using features of the input image. The
dictionary base... | computer science |
25,434 | Depth Fields: Extending Light Field Techniques to Time-of-Flight Imaging | cs.CV | A variety of techniques such as light field, structured illumination, and
time-of-flight (TOF) are commonly used for depth acquisition in consumer
imaging, robotics and many other applications. Unfortunately, each technique
suffers from its individual limitations preventing robust depth sensing. In
this paper, we explo... | computer science |
25,435 | A Novice Guide towards Human Motion Analysis and Understanding | cs.CV | Human motion analysis and understanding has been, and is still, the focus of
attention of many disciplines which is considered an obvious indicator of the
wide and massive importance of the subject. The purpose of this article is to
shed some light on this very important subject, so it can be a good insight for
a novic... | computer science |
25,436 | Vision-Based Road Detection using Contextual Blocks | cs.CV | Road detection is a fundamental task in autonomous navigation systems. In
this paper, we consider the case of monocular road detection, where images are
segmented into road and non-road regions. Our starting point is the well-known
machine learning approach, in which a classifier is trained to distinguish road
and non-... | computer science |
25,437 | Image Classification with Rejection using Contextual Information | cs.CV | We introduce a new supervised algorithm for image classification with
rejection using multiscale contextual information. Rejection is desired in
image-classification applications that require a robust classifier but not the
classification of the entire image. The proposed algorithm combines local and
multiscale context... | computer science |
25,438 | Semantic Amodal Segmentation | cs.CV | Common visual recognition tasks such as classification, object detection, and
semantic segmentation are rapidly reaching maturity, and given the recent rate
of progress, it is not unreasonable to conjecture that techniques for many of
these problems will approach human levels of performance in the next few years.
In th... | computer science |
25,439 | Learning Temporal Alignment Uncertainty for Efficient Event Detection | cs.CV | In this paper we tackle the problem of efficient video event detection. We
argue that linear detection functions should be preferred in this regard due to
their scalability and efficiency during estimation and evaluation. A popular
approach in this regard is to represent a sequence using a bag of words (BOW)
representa... | computer science |
25,440 | Conjugate Gradient Acceleration of Non-Linear Smoothing Filters | cs.CV | The most efficient signal edge-preserving smoothing filters, e.g., for
denoising, are non-linear. Thus, their acceleration is challenging and is often
performed in practice by tuning filter parameters, such as by increasing the
width of the local smoothing neighborhood, resulting in more aggressive
smoothing of a singl... | computer science |
25,441 | Object Recognition from Short Videos for Robotic Perception | cs.CV | Deep neural networks have become the primary learning technique for object
recognition. Videos, unlike still images, are temporally coherent which makes
the application of deep networks non-trivial. Here, we investigate how motion
can aid object recognition in short videos. Our approach is based on Long
Short-Term Memo... | computer science |
25,442 | Chebyshev and Conjugate Gradient Filters for Graph Image Denoising | cs.CV | In 3D image/video acquisition, different views are often captured with
varying noise levels across the views. In this paper, we propose a graph-based
image enhancement technique that uses a higher quality view to enhance a
degraded view. A depth map is utilized as auxiliary information to match the
perspectives of the ... | computer science |
25,443 | Co-interest Person Detection from Multiple Wearable Camera Videos | cs.CV | Wearable cameras, such as Google Glass and Go Pro, enable video data
collection over larger areas and from different views. In this paper, we tackle
a new problem of locating the co-interest person (CIP), i.e., the one who draws
attention from most camera wearers, from temporally synchronized videos taken
by multiple w... | computer science |
25,444 | Unsupervised Cross-Domain Recognition by Identifying Compact Joint
Subspaces | cs.CV | This paper introduces a new method to solve the cross-domain recognition
problem. Different from the traditional domain adaption methods which rely on a
global domain shift for all classes between source and target domain, the
proposed method is more flexible to capture individual class variations across
domains. By ad... | computer science |
25,445 | Joint Color-Spatial-Directional clustering and Region Merging (JCSD-RM)
for unsupervised RGB-D image segmentation | cs.CV | Recent advances in depth imaging sensors provide easy access to the
synchronized depth with color, called RGB-D image. In this paper, we propose an
unsupervised method for indoor RGB-D image segmentation and analysis. We
consider a statistical image generation model based on the color and geometry
of the scene. Our met... | computer science |
25,446 | An end-to-end generative framework for video segmentation and
recognition | cs.CV | We describe an end-to-end generative approach for the segmentation and
recognition of human activities. In this approach, a visual representation
based on reduced Fisher Vectors is combined with a structured temporal model
for recognition. We show that the statistical properties of Fisher Vectors make
them an especiall... | computer science |
25,447 | A New Low-Rank Tensor Model for Video Completion | cs.CV | In this paper, we propose a new low-rank tensor model based on the circulant
algebra, namely, twist tensor nuclear norm or t-TNN for short. The twist tensor
denotes a 3-way tensor representation to laterally store 2D data slices in
order. On one hand, t-TNN convexly relaxes the tensor multi-rank of the twist
tensor in ... | computer science |
25,448 | Future Localization from an Egocentric Depth Image | cs.CV | This paper presents a method for future localization: to predict a set of
plausible trajectories of ego-motion given a depth image. We predict paths
avoiding obstacles, between objects, even paths turning around a corner into
space behind objects. As a byproduct of the predicted trajectories of
ego-motion, we discover ... | computer science |
25,449 | Convexity Shape Constraints for Image Segmentation | cs.CV | Segmenting an image into multiple components is a central task in computer
vision. In many practical scenarios, prior knowledge about plausible components
is available. Incorporating such prior knowledge into models and algorithms for
image segmentation is highly desirable, yet can be non-trivial. In this work,
we intr... | computer science |
25,450 | Structured Prediction with Output Embeddings for Semantic Image
Annotation | cs.CV | We address the task of annotating images with semantic tuples. Solving this
problem requires an algorithm which is able to deal with hundreds of classes
for each argument of the tuple. In such contexts, data sparsity becomes a key
challenge, as there will be a large number of classes for which only a few
examples are a... | computer science |
25,451 | Object Proposals for Text Extraction in the Wild | cs.CV | Object Proposals is a recent computer vision technique receiving increasing
interest from the research community. Its main objective is to generate a
relatively small set of bounding box proposals that are most likely to contain
objects of interest. The use of Object Proposals techniques in the scene text
understanding... | computer science |
25,452 | HEp-2 Cell Classification: The Role of Gaussian Scale Space Theory as A
Pre-processing Approach | cs.CV | \textit{Indirect Immunofluorescence Imaging of Human Epithelial Type 2}
(HEp-2) cells is an effective way to identify the presence of Anti-Nuclear
Antibody (ANA). Most existing works on HEp-2 cell classification mainly focus
on feature extraction, feature encoding and classifier design. Very few efforts
have been devot... | computer science |
25,453 | Semantic Video Segmentation : Exploring Inference Efficiency | cs.CV | We explore the efficiency of the CRF inference beyond image level semantic
segmentation and perform joint inference in video frames. The key idea is to
combine best of two worlds: semantic co-labeling and more expressive models.
Our formulation enables us to perform inference over ten thousand images within
seconds and... | computer science |
25,454 | Accelerated graph-based spectral polynomial filters | cs.CV | Graph-based spectral denoising is a low-pass filtering using the
eigendecomposition of the graph Laplacian matrix of a noisy signal. Polynomial
filtering avoids costly computation of the eigendecomposition by projections
onto suitable Krylov subspaces. Polynomial filters can be based, e.g., on the
bilateral and guided ... | computer science |
25,455 | A Dual Fast and Slow Feature Interaction in Biologically Inspired Visual
Recognition of Human Action | cs.CV | Computational neuroscience studies that have examined human visual system
through functional magnetic resonance imaging (fMRI) have identified a model
where the mammalian brain pursues two distinct pathways (for recognition of
biological movement tasks). In the brain, dorsal stream analyzes the
information of motion (o... | computer science |
25,456 | Semantic Image Segmentation via Deep Parsing Network | cs.CV | This paper addresses semantic image segmentation by incorporating rich
information into Markov Random Field (MRF), including high-order relations and
mixture of label contexts. Unlike previous works that optimized MRFs using
iterative algorithm, we solve MRF by proposing a Convolutional Neural Network
(CNN), namely Dee... | computer science |
25,457 | Proposal-free Network for Instance-level Object Segmentation | cs.CV | Instance-level object segmentation is an important yet under-explored task.
The few existing studies are almost all based on region proposal methods to
extract candidate segments and then utilize object classification to produce
final results. Nonetheless, generating accurate region proposals itself is
quite challengin... | computer science |
25,458 | Shape Interaction Matrix Revisited and Robustified: Efficient Subspace
Clustering with Corrupted and Incomplete Data | cs.CV | The Shape Interaction Matrix (SIM) is one of the earliest approaches to
performing subspace clustering (i.e., separating points drawn from a union of
subspaces). In this paper, we revisit the SIM and reveal its connections to
several recent subspace clustering methods. Our analysis lets us derive a
simple, yet effectiv... | computer science |
25,459 | Dictionary Learning and Sparse Coding for Third-order Super-symmetric
Tensors | cs.CV | Super-symmetric tensors - a higher-order extension of scatter matrices - are
becoming increasingly popular in machine learning and computer vision for
modelling data statistics, co-occurrences, or even as visual descriptors.
However, the size of these tensors are exponential in the data dimensionality,
which is a signi... | computer science |
25,460 | Real-time Sign Language Fingerspelling Recognition using Convolutional
Neural Networks from Depth map | cs.CV | Sign language recognition is important for natural and convenient
communication between deaf community and hearing majority. We take the highly
efficient initial step of automatic fingerspelling recognition system using
convolutional neural networks (CNNs) from depth maps. In this work, we consider
relatively larger nu... | computer science |
25,461 | STC: A Simple to Complex Framework for Weakly-supervised Semantic
Segmentation | cs.CV | Recently, significant improvement has been made on semantic object
segmentation due to the development of deep convolutional neural networks
(DCNNs). Training such a DCNN usually relies on a large number of images with
pixel-level segmentation masks, and annotating these images is very costly in
terms of both finance a... | computer science |
25,462 | Learning Sparse Feature Representations using Probabilistic Quadtrees
and Deep Belief Nets | cs.CV | Learning sparse feature representations is a useful instrument for solving an
unsupervised learning problem. In this paper, we present three labeled
handwritten digit datasets, collectively called n-MNIST. Then, we propose a
novel framework for the classification of handwritten digits that learns sparse
representations... | computer science |
25,463 | A reliable order-statistics-based approximate nearest neighbor search
algorithm | cs.CV | We propose a new algorithm for fast approximate nearest neighbor search based
on the properties of ordered vectors. Data vectors are classified based on the
index and sign of their largest components, thereby partitioning the space in a
number of cones centered in the origin. The query is itself classified, and the
sea... | computer science |
25,464 | OCR accuracy improvement on document images through a novel
pre-processing approach | cs.CV | Digital camera and mobile document image acquisition are new trends arising
in the world of Optical Character Recognition and text detection. In some
cases, such process integrates many distortions and produces poorly scanned
text or text-photo images and natural images, leading to an unreliable OCR
digitization. In th... | computer science |
25,465 | Person Recognition in Personal Photo Collections | cs.CV | Recognising persons in everyday photos presents major challenges (occluded
faces, different clothing, locations, etc.) for machine vision. We propose a
convnet based person recognition system on which we provide an in-depth
analysis of informativeness of different body cues, impact of training data,
and the common fail... | computer science |
25,466 | Fingerprint Recognition Using Translation Invariant Scattering Network | cs.CV | Fingerprint recognition has drawn a lot of attention during last decades.
Different features and algorithms have been used for fingerprint recognition in
the past. In this paper, a powerful image representation called scattering
transform/network, is used for recognition. Scattering network is a
convolutional network w... | computer science |
25,467 | DeepSat - A Learning framework for Satellite Imagery | cs.CV | Satellite image classification is a challenging problem that lies at the
crossroads of remote sensing, computer vision, and machine learning. Due to the
high variability inherent in satellite data, most of the current object
classification approaches are not suitable for handling satellite datasets. The
progress of sat... | computer science |
25,468 | Oracle MCG: A first peek into COCO Detection Challenges | cs.CV | The recently presented COCO detection challenge will most probably be the
reference benchmark in object detection in the next years. COCO is two orders
of magnitude larger than Pascal and has four times the number of categories; so
in all likelihood researchers will be faced with a number of new challenges. At
this poi... | computer science |
25,469 | Learning Contextual Dependencies with Convolutional Hierarchical
Recurrent Neural Networks | cs.CV | Existing deep convolutional neural networks (CNNs) have shown their great
success on image classification. CNNs mainly consist of convolutional and
pooling layers, both of which are performed on local image areas without
considering the dependencies among different image regions. However, such
dependencies are very imp... | computer science |
25,470 | On Binary Classification with Single-Layer Convolutional Neural Networks | cs.CV | Convolutional neural networks are becoming standard tools for solving object
recognition and visual tasks. However, most of the design and implementation of
these complex models are based on trail-and-error. In this report, the main
focus is to consider some of the important factors in designing convolutional
networks ... | computer science |
25,471 | Learning to Divide and Conquer for Online Multi-Target Tracking | cs.CV | Online Multiple Target Tracking (MTT) is often addressed within the
tracking-by-detection paradigm. Detections are previously extracted
independently in each frame and then objects trajectories are built by
maximizing specifically designed coherence functions. Nevertheless, ambiguities
arise in presence of occlusions o... | computer science |
25,472 | Expanded Parts Model for Semantic Description of Humans in Still Images | cs.CV | We introduce an Expanded Parts Model (EPM) for recognizing human attributes
(e.g. young, short hair, wearing suit) and actions (e.g. running, jumping) in
still images. An EPM is a collection of part templates which are learnt
discriminatively to explain specific scale-space regions in the images (in
human centric coord... | computer science |
25,473 | gSLICr: SLIC superpixels at over 250Hz | cs.CV | We introduce a parallel GPU implementation of the Simple Linear Iterative
Clustering (SLIC) superpixel segmentation. Using a single graphic card, our
implementation achieves speedups of up to $83\times$ from the standard
sequential implementation. Our implementation is fully compatible with the
standard sequential impl... | computer science |
25,474 | Sparse Representation for 3D Shape Estimation: A Convex Relaxation
Approach | cs.CV | We investigate the problem of estimating the 3D shape of an object defined by
a set of 3D landmarks, given their 2D correspondences in a single image. A
successful approach to alleviating the reconstruction ambiguity is the 3D
deformable shape model and a sparse representation is often used to capture
complex shape var... | computer science |
25,475 | Analyzing structural characteristics of object category representations
from their semantic-part distributions | cs.CV | Studies from neuroscience show that part-mapping computations are employed by
human visual system in the process of object recognition. In this work, we
present an approach for analyzing semantic-part characteristics of object
category representations. For our experiments, we use category-epitome, a
recently proposed s... | computer science |
25,476 | Medical Image Classification via SVM using LBP Features from
Saliency-Based Folded Data | cs.CV | Good results on image classification and retrieval using support vector
machines (SVM) with local binary patterns (LBPs) as features have been
extensively reported in the literature where an entire image is retrieved or
classified. In contrast, in medical imaging, not all parts of the image may be
equally significant o... | computer science |
25,477 | Self-Configuring and Evolving Fuzzy Image Thresholding | cs.CV | Every segmentation algorithm has parameters that need to be adjusted in order
to achieve good results. Evolving fuzzy systems for adjustment of segmentation
parameters have been proposed recently (Evolving fuzzy image segmentation --
EFIS [1]. However, similar to any other algorithm, EFIS too suffers from a few
limitat... | computer science |
25,478 | SPECFACE - A Dataset of Human Faces Wearing Spectacles | cs.CV | This paper presents a database of human faces for persons wearing spectacles.
The database consists of images of faces having significant variations with
respect to illumination, head pose, skin color, facial expressions and sizes,
and nature of spectacles. The database contains data of 60 subjects. This
database is ex... | computer science |
25,479 | DenseBox: Unifying Landmark Localization with End to End Object
Detection | cs.CV | How can a single fully convolutional neural network (FCN) perform on object
detection? We introduce DenseBox, a unified end-to-end FCN framework that
directly predicts bounding boxes and object class confidences through all
locations and scales of an image. Our contribution is two-fold. First, we show
that a single FCN... | computer science |
25,480 | An Improved Algorithm for Eye Corner Detection | cs.CV | In this paper, a modified algorithm for the detection of nasal and temporal
eye corners is presented. The algorithm is a modification of the Santos and
Proenka Method. In the first step, we detect the face and the eyes using
classifiers based on Haar-like features. We then segment out the sclera, from
the detected eye ... | computer science |
25,481 | Projection Bank: From High-dimensional Data to Medium-length Binary
Codes | cs.CV | Recently, very high-dimensional feature representations, e.g., Fisher Vector,
have achieved excellent performance for visual recognition and retrieval.
However, these lengthy representations always cause extremely heavy
computational and storage costs and even become unfeasible in some large-scale
applications. A few e... | computer science |
25,482 | Guiding Long-Short Term Memory for Image Caption Generation | cs.CV | In this work we focus on the problem of image caption generation. We propose
an extension of the long short term memory (LSTM) model, which we coin gLSTM
for short. In particular, we add semantic information extracted from the image
as extra input to each unit of the LSTM block, with the aim of guiding the
model toward... | computer science |
25,483 | Human and Sheep Facial Landmarks Localisation by Triplet Interpolated
Features | cs.CV | In this paper we present a method for localisation of facial landmarks on
human and sheep. We introduce a new feature extraction scheme called
triplet-interpolated feature used at each iteration of the cascaded shape
regression framework. It is able to extract features from similar semantic
location given an estimated ... | computer science |
25,484 | Overcomplete Dictionary Learning with Jacobi Atom Updates | cs.CV | Dictionary learning for sparse representations is traditionally approached
with sequential atom updates, in which an optimized atom is used immediately
for the optimization of the next atoms. We propose instead a Jacobi version, in
which groups of atoms are updated independently, in parallel. Extensive
numerical eviden... | computer science |
25,485 | Accelerated Distance Computation with Encoding Tree for High Dimensional
Data | cs.CV | We propose a novel distance to calculate distance between high dimensional
vector pairs, utilizing vector quantization generated encodings. Vector
quantization based methods are successful in handling large scale high
dimensional data. These methods compress vectors into short encodings, and
allow efficient distance co... | computer science |
25,486 | HCLAE: High Capacity Locally Aggregating Encodings for Approximate
Nearest Neighbor Search | cs.CV | Vector quantization-based approaches are successful to solve Approximate
Nearest Neighbor (ANN) problems which are critical to many applications. The
idea is to generate effective encodings to allow fast distance approximation.
We propose quantization-based methods should partition the data space finely
and exhibit loc... | computer science |
25,487 | Improved Residual Vector Quantization for High-dimensional Approximate
Nearest Neighbor Search | cs.CV | Quantization methods have been introduced to perform large scale approximate
nearest search tasks. Residual Vector Quantization (RVQ) is one of the
effective quantization methods. RVQ uses a multi-stage codebook learning scheme
to lower the quantization error stage by stage. However, there are two major
limitations for... | computer science |
25,488 | Hand-held Video Deblurring via Efficient Fourier Aggregation | cs.CV | Videos captured with hand-held cameras often suffer from a significant amount
of blur, mainly caused by the inevitable natural tremor of the photographer's
hand. In this work, we present an algorithm that removes blur due to camera
shake by combining information in the Fourier domain from nearby frames in a
video. The ... | computer science |
25,489 | Deep Multi-task Learning for Railway Track Inspection | cs.CV | Railroad tracks need to be periodically inspected and monitored to ensure
safe transportation. Automated track inspection using computer vision and
pattern recognition methods have recently shown the potential to improve safety
by allowing for more frequent inspections while reducing human errors.
Achieving full automa... | computer science |
25,490 | Recurrent Spatial Transformer Networks | cs.CV | We integrate the recently proposed spatial transformer network (SPN)
[Jaderberg et. al 2015] into a recurrent neural network (RNN) to form an
RNN-SPN model. We use the RNN-SPN to classify digits in cluttered MNIST
sequences. The proposed model achieves a single digit error of 1.5% compared to
2.9% for a convolutional n... | computer science |
25,491 | Geometry-aware Deep Transform | cs.CV | Many recent efforts have been devoted to designing sophisticated deep
learning structures, obtaining revolutionary results on benchmark datasets. The
success of these deep learning methods mostly relies on an enormous volume of
labeled training samples to learn a huge number of parameters in a network;
therefore, under... | computer science |
25,492 | Facial Descriptors for Human Interaction Recognition In Still Images | cs.CV | This paper presents a novel approach in a rarely studied area of computer
vision: Human interaction recognition in still images. We explore whether the
facial regions and their spatial configurations contribute to the recognition
of interactions. In this respect, our method involves extraction of several
visual feature... | computer science |
25,493 | An Experimental Survey on Correlation Filter-based Tracking | cs.CV | Over these years, Correlation Filter-based Trackers (CFTs) have aroused
increasing interests in the field of visual object tracking, and have achieved
extremely compelling results in different competitions and benchmarks. In this
paper, our goal is to review the developments of CFTs with extensive
experimental results.... | computer science |
25,494 | Efficient Clustering on Riemannian Manifolds: A Kernelised Random
Projection Approach | cs.CV | Reformulating computer vision problems over Riemannian manifolds has
demonstrated superior performance in various computer vision applications. This
is because visual data often forms a special structure lying on a lower
dimensional space embedded in a higher dimensional space. However, since these
manifolds belong to ... | computer science |
25,495 | Linearized Kernel Dictionary Learning | cs.CV | In this paper we present a new approach of incorporating kernels into
dictionary learning. The kernel K-SVD algorithm (KKSVD), which has been
introduced recently, shows an improvement in classification performance, with
relation to its linear counterpart K-SVD. However, this algorithm requires the
storage and handling ... | computer science |
25,496 | Similar Handwritten Chinese Character Discrimination by Weakly
Supervised Learning | cs.CV | Traditional approaches for handwritten Chinese character recognition suffer
in classifying similar characters. In this paper, we propose to discriminate
similar handwritten Chinese characters by using weakly supervised learning. Our
approach learns a discriminative SVM for each similar pair which simultaneously
localiz... | computer science |
25,497 | Face Photo Sketch Synthesis via Larger Patch and Multiresolution Spline | cs.CV | Face photo sketch synthesis has got some researchers' attention in recent
years because of its potential applications in digital entertainment and law
enforcement. Some patches based methods have been proposed to solve this
problem. These methods usually focus more on how to get a sketch patch for a
given photo patch t... | computer science |
25,498 | Robust Visual Tracking via Inverse Nonnegative Matrix Factorization | cs.CV | The establishment of robust target appearance model over time is an
overriding concern in visual tracking. In this paper, we propose an inverse
nonnegative matrix factorization (NMF) method for robust appearance modeling.
Rather than using a linear combination of nonnegative basis matrices for each
target image patch i... | computer science |
25,499 | A Parallel Framework for Parametric Maximum Flow Problems in Image
Segmentation | cs.CV | This paper presents a framework that supports the implementation of parallel
solutions for the widespread parametric maximum flow computational routines
used in image segmentation algorithms. The framework is based on supergraphs, a
special construction combining several image graphs into a larger one, and
works on var... | computer science |
25,500 | Image Set Querying Based Localization | cs.CV | Conventional single image based localization methods usually fail to localize
a querying image when there exist large variations between the querying image
and the pre-built scene. To address this, we propose an image-set querying
based localization approach. When the localization by a single image fails to
work, the s... | computer science |
25,501 | Deep Convolutional Features for Image Based Retrieval and Scene
Categorization | cs.CV | Several recent approaches showed how the representations learned by
Convolutional Neural Networks can be repurposed for novel tasks. Most commonly
it has been shown that the activation features of the last fully connected
layers (fc7 or fc6) of the network, followed by a linear classifier outperform
the state-of-the-ar... | computer science |
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