Unnamed: 0 int64 0 41k | title stringlengths 4 274 | category stringlengths 5 18 | summary stringlengths 22 3.66k | theme stringclasses 8
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24,502 | Maximum Margin Vector Correlation Filter | cs.CV | Correlation Filters (CFs) are a class of classifiers which are designed for
accurate pattern localization. Traditionally CFs have been used with scalar
features only, which limits their ability to be used with vector feature
representations like Gabor filter banks, SIFT, HOG, etc. In this paper we
present a new CF name... | computer science |
24,503 | A General Homogeneous Matrix Formulation to 3D Rotation Geometric
Transformations | cs.CV | We present algebraic projective geometry definitions of 3D rotations so as to
bridge a small gap between the applications and the definitions of 3D rotations
in homogeneous matrix form. A general homogeneous matrix formulation to 3D
rotation geometric transformations is proposed which suits for the cases when
the rotat... | computer science |
24,504 | Improving weather radar by fusion and classification | cs.CV | In air traffic management (ATM) all necessary operations (tactical planing,
sector configuration, required staffing, runway configuration, routing of
approaching aircrafts) rely on accurate measurements and predictions of the
current weather situation. An essential basis of information is delivered by
weather radar ima... | computer science |
24,505 | Indoor Activity Detection and Recognition for Sport Games Analysis | cs.CV | Activity recognition in sport is an attractive field for computer vision
research. Game, player and team analysis are of great interest and research
topics within this field emerge with the goal of automated analysis. The very
specific underlying rules of sports can be used as prior knowledge for the
recognition task a... | computer science |
24,506 | Robust and Efficient Subspace Segmentation via Least Squares Regression | cs.CV | This paper studies the subspace segmentation problem which aims to segment
data drawn from a union of multiple linear subspaces. Recent works by using
sparse representation, low rank representation and their extensions attract
much attention. If the subspaces from which the data drawn are independent or
orthogonal, the... | computer science |
24,507 | Stereo on a budget | cs.CV | We propose an algorithm for recovering depth using less than two images.
Instead of having both cameras send their entire image to the host computer,
the left camera sends its image to the host while the right camera sends only a
fraction $\epsilon$ of its image. The key aspect is that the cameras send the
information ... | computer science |
24,508 | Computer vision-based recognition of liquid surfaces and phase
boundaries in transparent vessels, with emphasis on chemistry applications | cs.CV | The ability to recognize the liquid surface and the liquid level in
transparent containers is perhaps the most commonly used evaluation method when
dealing with fluids. Such recognition is essential in determining the liquid
volume, fill level, phase boundaries and phase separation in various fluid
systems. The recogni... | computer science |
24,509 | Spatially Directional Predictive Coding for Block-based Compressive
Sensing of Natural Images | cs.CV | A novel coding strategy for block-based compressive sens-ing named spatially
directional predictive coding (SDPC) is proposed, which efficiently utilizes
the intrinsic spatial cor-relation of natural images. At the encoder, for each
block of compressive sensing (CS) measurements, the optimal pre-diction is
selected fro... | computer science |
24,510 | Structural Group Sparse Representation for Image Compressive Sensing
Recovery | cs.CV | Compressive Sensing (CS) theory shows that a signal can be decoded from many
fewer measurements than suggested by the Nyquist sampling theory, when the
signal is sparse in some domain. Most of conventional CS recovery approaches,
however, exploited a set of fixed bases (e.g. DCT, wavelet, contourlet and
gradient domain... | computer science |
24,511 | Image Compressive Sensing Recovery Using Adaptively Learned Sparsifying
Basis via L0 Minimization | cs.CV | From many fewer acquired measurements than suggested by the Nyquist sampling
theory, compressive sensing (CS) theory demonstrates that, a signal can be
reconstructed with high probability when it exhibits sparsity in some domain.
Most of the conventional CS recovery approaches, however, exploited a set of
fixed bases (... | computer science |
24,512 | High-Speed Tracking with Kernelized Correlation Filters | cs.CV | The core component of most modern trackers is a discriminative classifier,
tasked with distinguishing between the target and the surrounding environment.
To cope with natural image changes, this classifier is typically trained with
translated and scaled sample patches. Such sets of samples are riddled with
redundancies... | computer science |
24,513 | Dynamic Mode Decomposition for Real-Time Background/Foreground
Separation in Video | cs.CV | This paper introduces the method of dynamic mode decomposition (DMD) for
robustly separating video frames into background (low-rank) and foreground
(sparse) components in real-time. The method is a novel application of a
technique used for characterizing nonlinear dynamical systems in an
equation-free manner by decompo... | computer science |
24,514 | Selecting a Small Set of Optimal Gestures from an Extensive Lexicon | cs.CV | Finding the best set of gestures to use for a given computer recognition
problem is an essential part of optimizing the recognition performance while
being mindful to those who may articulate the gestures. An objective function,
called the ellipsoidal distance ratio metric (EDRM), for determining the best
gestures from... | computer science |
24,515 | A graph-based mathematical morphology reader | cs.CV | This survey paper aims at providing a "literary" anthology of mathematical
morphology on graphs. It describes in the English language many ideas stemming
from a large number of different papers, hence providing a unified view of an
active and diverse field of research. | computer science |
24,516 | Pixel-wise Orthogonal Decomposition for Color Illumination Invariant and
Shadow-free Image | cs.CV | In this paper, we propose a novel, effective and fast method to obtain a
color illumination invariant and shadow-free image from a single outdoor image.
Different from state-of-the-art methods for shadow-free image that either need
shadow detection or statistical learning, we set up a linear equation set for
each pixel... | computer science |
24,517 | Deep Poselets for Human Detection | cs.CV | We address the problem of detecting people in natural scenes using a part
approach based on poselets. We propose a bootstrapping method that allows us to
collect millions of weakly labeled examples for each poselet type. We use these
examples to train a Convolutional Neural Net to discriminate different poselet
types a... | computer science |
24,518 | BiofilmQuant: A Computer-Assisted Tool for Dental Biofilm Quantification | cs.CV | Dental biofilm is the deposition of microbial material over a tooth
substratum. Several methods have recently been reported in the literature for
biofilm quantification; however, at best they provide a barely automated
solution requiring significant input needed from the human expert. On the
contrary, state-of-the-art ... | computer science |
24,519 | Strengthening the Effectiveness of Pedestrian Detection with Spatially
Pooled Features | cs.CV | We propose a simple yet effective approach to the problem of pedestrian
detection which outperforms the current state-of-the-art. Our new features are
built on the basis of low-level visual features and spatial pooling.
Incorporating spatial pooling improves the translational invariance and thus
the robustness of the d... | computer science |
24,520 | Multiple Moving Object Recognitions in video based on Log Gabor-PCA
Approach | cs.CV | Object recognition in the video sequence or images is one of the sub-field of
computer vision. Moving object recognition from a video sequence is an
appealing topic with applications in various areas such as airport safety,
intrusion surveillance, video monitoring, intelligent highway, etc. Moving
object recognition is... | computer science |
24,521 | From Manifold to Manifold: Geometry-Aware Dimensionality Reduction for
SPD Matrices | cs.CV | Representing images and videos with Symmetric Positive Definite (SPD)
matrices and considering the Riemannian geometry of the resulting space has
proven beneficial for many recognition tasks. Unfortunately, computation on the
Riemannian manifold of SPD matrices --especially of high-dimensional ones--
comes at a high co... | computer science |
24,522 | Calibration of Multiple Fish-Eye Cameras Using a Wand | cs.CV | Fish-eye cameras are becoming increasingly popular in computer vision, but
their use for 3D measurement is limited partly due to the lack of an accurate,
efficient and user-friendly calibration procedure. For such a purpose, we
propose a method to calibrate the intrinsic and extrinsic parameters (including
radial disto... | computer science |
24,523 | Homophilic Clustering by Locally Asymmetric Geometry | cs.CV | Clustering is indispensable for data analysis in many scientific disciplines.
Detecting clusters from heavy noise remains challenging, particularly for
high-dimensional sparse data. Based on graph-theoretic framework, the present
paper proposes a novel algorithm to address this issue. The locally asymmetric
geometries ... | computer science |
24,524 | Large-scale Supervised Hierarchical Feature Learning for Face
Recognition | cs.CV | This paper proposes a novel face recognition algorithm based on large-scale
supervised hierarchical feature learning. The approach consists of two parts:
hierarchical feature learning and large-scale model learning. The hierarchical
feature learning searches feature in three levels of granularity in a
supervised way. F... | computer science |
24,525 | Novel methods for multilinear data completion and de-noising based on
tensor-SVD | cs.CV | In this paper we propose novel methods for completion (from limited samples)
and de-noising of multilinear (tensor) data and as an application consider 3-D
and 4- D (color) video data completion and de-noising. We exploit the recently
proposed tensor-Singular Value Decomposition (t-SVD)[11]. Based on t-SVD, the
notion ... | computer science |
24,526 | Simultaneous Detection and Segmentation | cs.CV | We aim to detect all instances of a category in an image and, for each
instance, mark the pixels that belong to it. We call this task Simultaneous
Detection and Segmentation (SDS). Unlike classical bounding box detection, SDS
requires a segmentation and not just a box. Unlike classical semantic
segmentation, we require... | computer science |
24,527 | Regression-Based Image Alignment for General Object Categories | cs.CV | Gradient-descent methods have exhibited fast and reliable performance for
image alignment in the facial domain, but have largely been ignored by the
broader vision community. They require the image function be smooth and
(numerically) differentiable -- properties that hold for pixel-based
representations obeying natura... | computer science |
24,528 | Learning Discriminative Stein Kernel for SPD Matrices and Its
Applications | cs.CV | Stein kernel has recently shown promising performance on classifying images
represented by symmetric positive definite (SPD) matrices. It evaluates the
similarity between two SPD matrices through their eigenvalues. In this paper,
we argue that directly using the original eigenvalues may be problematic
because: i) Eigen... | computer science |
24,529 | Orientation covariant aggregation of local descriptors with embeddings | cs.CV | Image search systems based on local descriptors typically achieve orientation
invariance by aligning the patches on their dominant orientations. Albeit
successful, this choice introduces too much invariance because it does not
guarantee that the patches are rotated consistently. This paper introduces an
aggregation str... | computer science |
24,530 | Fast Separable Non-Local Means | cs.CV | We propose a simple and fast algorithm called PatchLift for computing
distances between patches (contiguous block of samples) extracted from a given
one-dimensional signal. PatchLift is based on the observation that the patch
distances can be efficiently computed from a matrix that is derived from the
one-dimensional s... | computer science |
24,531 | Online Stroke and Akshara Recognition GUI in Assamese Language Using
Hidden Markov Model | cs.CV | The work describes the development of Online Assamese Stroke & Akshara
Recognizer based on a set of language rules. In handwriting literature strokes
are composed of two coordinate trace in between pen down and pen up labels. The
Assamese aksharas are combination of a number of strokes, the maximum number of
strokes ta... | computer science |
24,532 | Classifiers fusion method to recognize handwritten persian numerals | cs.CV | Recognition of Persian handwritten characters has been considered as a
significant field of research for the last few years under pattern analysing
technique. In this paper, a new approach for robust handwritten Persian
numerals recognition using strong feature set and a classifier fusion method is
scrutinized to incre... | computer science |
24,533 | A Statistical Modeling Approach to Computer-Aided Quantification of
Dental Biofilm | cs.CV | Biofilm is a formation of microbial material on tooth substrata. Several
methods to quantify dental biofilm coverage have recently been reported in the
literature, but at best they provide a semi-automated approach to
quantification with significant input from a human grader that comes with the
graders bias of what are... | computer science |
24,534 | Classifying Fonts and Calligraphy Styles Using Complex Wavelet Transform | cs.CV | Recognizing fonts has become an important task in document analysis, due to
the increasing number of available digital documents in different fonts and
emphases. A generic font-recognition system independent of language, script and
content is desirable for processing various types of documents. At the same
time, catego... | computer science |
24,535 | Offline handwritten signature identification using adaptive window
positioning techniques | cs.CV | The paper presents to address this challenge, we have proposed the use of
Adaptive Window Positioning technique which focuses on not just the meaning of
the handwritten signature but also on the individuality of the writer. This
innovative technique divides the handwritten signature into 13 small windows of
size nxn(13... | computer science |
24,536 | ARTOS -- Adaptive Real-Time Object Detection System | cs.CV | ARTOS is all about creating, tuning, and applying object detection models
with just a few clicks. In particular, ARTOS facilitates learning of models for
visual object detection by eliminating the burden of having to collect and
annotate a large set of positive and negative samples manually and in addition
it implement... | computer science |
24,537 | On the Convergence of the Mean Shift Algorithm in the One-Dimensional
Space | cs.CV | The mean shift algorithm is a non-parametric and iterative technique that has
been used for finding modes of an estimated probability density function. It
has been successfully employed in many applications in specific areas of
machine vision, pattern recognition, and image processing. Although the mean
shift algorithm... | computer science |
24,538 | CIDI-Lung-Seg: A Single-Click Annotation Tool for Automatic Delineation
of Lungs from CT Scans | cs.CV | Accurate and fast extraction of lung volumes from computed tomography (CT)
scans remains in a great demand in the clinical environment because the
available methods fail to provide a generic solution due to wide anatomical
variations of lungs and existence of pathologies. Manual annotation, current
gold standard, is ti... | computer science |
24,539 | Near-optimal Keypoint Sampling for Fast Pathological Lung Segmentation | cs.CV | Accurate delineation of pathological lungs from computed tomography (CT)
images remains mostly unsolved because available methods fail to provide a
reliable generic solution due to high variability of abnormality appearance.
Local descriptor-based classification methods have shown to work well in
annotating pathologies... | computer science |
24,540 | Optimally Stabilized PET Image Denoising Using Trilateral Filtering | cs.CV | Low-resolution and signal-dependent noise distribution in positron emission
tomography (PET) images makes denoising process an inevitable step prior to
qualitative and quantitative image analysis tasks. Conventional PET denoising
methods either over-smooth small-sized structures due to resolution limitation
or make inc... | computer science |
24,541 | Articulated Pose Estimation by a Graphical Model with Image Dependent
Pairwise Relations | cs.CV | We present a method for estimating articulated human pose from a single
static image based on a graphical model with novel pairwise relations that make
adaptive use of local image measurements. More precisely, we specify a
graphical model for human pose which exploits the fact the local image
measurements can be used b... | computer science |
24,542 | Optimizing Auto-correlation for Fast Target Search in Large Search Space | cs.CV | In remote sensing image-blurring is induced by many sources such as
atmospheric scatter, optical aberration, spatial and temporal sensor
integration. The natural blurring can be exploited to speed up target search by
fast template matching. In this paper, we synthetically induce additional
non-uniform blurring to furth... | computer science |
24,543 | Measuring Atmospheric Scattering from Digital Images of Urban Scenery
using Temporal Polarization-Based Vision | cs.CV | Particulate Matter (PM) is a form of air pollution that visually degrades
urban scenery and is hazardous to human health and the environment. Current
monitoring devices are limited in measuring average PM over large areas.
Quantifying the visual effects of haze in digital images of urban scenery and
correlating these e... | computer science |
24,544 | An Enhancement Neighborhood connected Segmentation for 2D-Cellular Image | cs.CV | A good segmentation result depends on a set of "correct" choice for the
seeds. When the input images are noisy, the seeds may fall on atypical pixels
that are not representative of the region statistics. This can lead to
erroneous segmentation results. In this paper, an automatic seeded region
growing algorithm is prop... | computer science |
24,545 | Enhanced EZW Technique for Compression of Image by Setting Detail
Retaining Pass Number | cs.CV | This submission has been withdrawn by arXiv administrators because it
contains excessive and unattributed reuse of content from other authors. | computer science |
24,546 | A New Approach for Super resolution by Using Web Images and FFT Based
Image Registration | cs.CV | Preserving accuracy is a challenging issue in super resolution images. In
this paper, we propose a new FFT based image registration algorithm and a
sparse based super resolution algorithm to improve the accuracy of super
resolution image. Given a low resolution image, our approach initially extracts
the local descripto... | computer science |
24,547 | Spatiotemporal Stacked Sequential Learning for Pedestrian Detection | cs.CV | Pedestrian classifiers decide which image windows contain a pedestrian. In
practice, such classifiers provide a relatively high response at neighbor
windows overlapping a pedestrian, while the responses around potential false
positives are expected to be lower. An analogous reasoning applies for image
sequences. If the... | computer science |
24,548 | Recovery of Images with Missing Pixels using a Gradient Compressive
Sensing Algorithm | cs.CV | This paper investigates the possibility of reconstruction of images
considering that they are sparse in the DCT transformation domain. Two
approaches are considered. One when the image is pre-processed in the DCT
domain, using 8x8 blocks. The image is made sparse by setting the smallest DCT
coefficients to zero. In the... | computer science |
24,549 | Depth Reconstruction from Sparse Samples: Representation, Algorithm, and
Sampling | cs.CV | The rapid development of 3D technology and computer vision applications have
motivated a thrust of methodologies for depth acquisition and estimation.
However, most existing hardware and software methods have limited performance
due to poor depth precision, low resolution and high computational cost. In
this paper, we ... | computer science |
24,550 | Part-based R-CNNs for Fine-grained Category Detection | cs.CV | Semantic part localization can facilitate fine-grained categorization by
explicitly isolating subtle appearance differences associated with specific
object parts. Methods for pose-normalized representations have been proposed,
but generally presume bounding box annotations at test time due to the
difficulty of object d... | computer science |
24,551 | Globally Optimal Joint Image Segmentation and Shape Matching Based on
Wasserstein Modes | cs.CV | A functional for joint variational object segmentation and shape matching is
developed. The formulation is based on optimal transport w.r.t. geometric
distance and local feature similarity. Geometric invariance and modelling of
object-typical statistical variations is achieved by introducing degrees of
freedom that des... | computer science |
24,552 | An iterative approach to Hough transform without re-voting | cs.CV | Many bone shapes in the human skeleton are characterized by profiles that can
be associated to equations of algebraic curves. Fixing the parameters in the
curve equation, by means of a classical pattern recognition procedure like the
Hough transform technique, it is then possible to associate an equation to a
specific ... | computer science |
24,553 | Image Fusion Using LEP Filtering and Bilinear Interpolation | cs.CV | Image Fusion is the process in which core information from a set of component
images is merged to form a single image, which is more informative and complete
than the component input images in quality and appearance. This paper presents
a fast and effective image fusion method for creating high quality fused images
by ... | computer science |
24,554 | Aggregate channel features for multi-view face detection | cs.CV | Face detection has drawn much attention in recent decades since the seminal
work by Viola and Jones. While many subsequences have improved the work with
more powerful learning algorithms, the feature representation used for face
detection still can't meet the demand for effectively and efficiently handling
faces with l... | computer science |
24,555 | Mobile Camera Array Calibration for Light Field Acquisition | cs.CV | The light field camera is useful for computer graphics and vision
applications. Calibration is an essential step for these applications. After
calibration, we can rectify the captured image by using the calibrated camera
parameters. However, the large camera array calibration method, which assumes
that all cameras are ... | computer science |
24,556 | Analysis of Gait Pattern to Recognize the Human Activities | cs.CV | Human activity recognition based on the computer vision is the process of
labelling image sequences with action labels. Accurate systems for this problem
are applied in areas such as visual surveillance, human computer interaction
and video retrieval. | computer science |
24,557 | Affine Subspace Representation for Feature Description | cs.CV | This paper proposes a novel Affine Subspace Representation (ASR) descriptor
to deal with affine distortions induced by viewpoint changes. Unlike the
traditional local descriptors such as SIFT, ASR inherently encodes local
information of multi-view patches, making it robust to affine distortions while
maintaining a high... | computer science |
24,558 | Hand Pointing Detection Using Live Histogram Template of Forehead Skin | cs.CV | Hand pointing detection has multiple applications in many fields such as
virtual reality and control devices in smart homes. In this paper, we proposed
a novel approach to detect pointing vector in 2D space of a room. After
background subtraction, face and forehead is detected. In the second step,
forehead skin H-S pla... | computer science |
24,559 | LSDA: Large Scale Detection Through Adaptation | cs.CV | A major challenge in scaling object detection is the difficulty of obtaining
labeled images for large numbers of categories. Recently, deep convolutional
neural networks (CNNs) have emerged as clear winners on object classification
benchmarks, in part due to training with 1.2M+ labeled classification images.
Unfortunat... | computer science |
24,560 | Object Proposal Generation using Two-Stage Cascade SVMs | cs.CV | Object proposal algorithms have shown great promise as a first step for
object recognition and detection. Good object proposal generation algorithms
require high object recall rate as well as low computational cost, because
generating object proposals is usually utilized as a preprocessing step. The
problem of how to a... | computer science |
24,561 | Optimized Method for Iranian Road Signs Detection and recognition system | cs.CV | Road sign recognition is one of the core technologies in Intelligent
Transport Systems. In the current study, a robust and real-time method is
presented to identify and detect the roads speed signs in road image in
different situations. In our proposed method, first, the connected components
are created in the main ima... | computer science |
24,562 | Aggregation of local parametric candidates with exemplar-based occlusion
handling for optical flow | cs.CV | Handling all together large displacements, motion details and occlusions
remains an open issue for reliable computation of optical flow in a video
sequence. We propose a two-step aggregation paradigm to address this problem.
The idea is to supply local motion candidates at every pixel in a first step,
and then to combi... | computer science |
24,563 | Detection of Sclerotic Spine Metastases via Random Aggregation of Deep
Convolutional Neural Network Classifications | cs.CV | Automated detection of sclerotic metastases (bone lesions) in Computed
Tomography (CT) images has potential to be an important tool in clinical
practice and research. State-of-the-art methods show performance of 79%
sensitivity or true-positive (TP) rate, at 10 false-positives (FP) per volume.
We design a two-tiered co... | computer science |
24,564 | Joint Energy-based Detection and Classificationon of Multilingual Text
Lines | cs.CV | This paper proposes a new hierarchical MDL-based model for a joint detection
and classification of multilingual text lines in im- ages taken by hand-held
cameras. The majority of related text detec- tion methods assume alphabet-based
writing in a single language, e.g. in Latin. They use simple clustering
heuristics spe... | computer science |
24,565 | Visual Word Selection without Re-Coding and Re-Pooling | cs.CV | The Bag-of-Words (BoW) representation is widely used in computer vision. The
size of the codebook impacts the time and space complexity of the applications
that use BoW. Thus, given a training set for a particular computer vision task,
a key problem is pruning a large codebook to select only a subset of visual
words. E... | computer science |
24,566 | FollowMe: Efficient Online Min-Cost Flow Tracking with Bounded Memory
and Computation | cs.CV | One of the most popular approaches to multi-target tracking is
tracking-by-detection. Current min-cost flow algorithms which solve the data
association problem optimally have three main drawbacks: they are
computationally expensive, they assume that the whole video is given as a
batch, and they scale badly in memory an... | computer science |
24,567 | A robust and adaptable method for face detection based on Color
Probabilistic Estimation Technique | cs.CV | Human face perception is currently an active research area in the computer
vision community. Skin detection is one of the most important and primary
stages for this purpose. So far, many approaches are proposed to done this
case. Near all of these methods have tried to find best match intensity
distribution with skin p... | computer science |
24,568 | Novel and Automatic Parking Inventory System Based on Pattern
Recognition and Directional Chain Code | cs.CV | The objective of this paper is to design an efficient vehicle license plate
recognition System and to implement it for automatic parking inventory system.
The system detects the vehicle first and then captures the image of the front
view of the vehicle. Vehicle license plate is localized and characters are
segmented. F... | computer science |
24,569 | Performance evaluation of wavelet scattering network in image texture
classification in various color spaces | cs.CV | Texture plays an important role in many image analysis applications. In this
paper, we give a performance evaluation of color texture classification by
performing wavelet scattering network in various color spaces. Experimental
results on the KTH_TIPS_COL database show that opponent RGB based wavelet
scattering network... | computer science |
24,570 | Recognition of Handwritten Persian/Arabic Numerals Based on Robust
Feature Set and K-NN Classifier | cs.CV | This paper has been withdrawn by the author due to a crucial sign error in
equation 2 and some mistake in Table 1 information. please let me for changing
this information and updating this paper. | computer science |
24,571 | Novel and Fast Algorithm for Extracting License Plate Location Based on
Edge Analysis | cs.CV | Nowadays in developing or developed countries, the Intelligent Transportation
System (ITS) technology has attracted so much attention to itself. License
Plate Recognition (LPR) systems have many applications in ITSs, such as the
payment of parking fee, controlling the traffic volume, traffic data
collection, etc. This ... | computer science |
24,572 | Real-Time and Efficient Method for Accuracy Enhancement of Edge Based
License Plate Recognition System | cs.CV | License Plate Recognition plays an important role on the traffic monitoring
and parking management. Administration and restriction of those transportation
tools for their better service becomes very essential. In this paper, a fast
and real time method has an appropriate application to find plates that the
plat has til... | computer science |
24,573 | Novel and Tuneable Method for Skin Detection Based on Hybrid Color Space
and Color Statistical Features | cs.CV | Skin detection is one of the most important and primary stages in some of
image processing applications such as face detection and human tracking. So
far, many approaches are proposed to done this case. Near all of these methods
have tried to find best match intensity distribution with skin pixels based on
popular colo... | computer science |
24,574 | New Method for Optimization of License Plate Recognition system with Use
of Edge Detection and Connected Component | cs.CV | License Plate recognition plays an important role on the traffic monitoring
and parking management systems. In this paper, a fast and real time method has
been proposed which has an appropriate application to find tilt and poor
quality plates. In the proposed method, at the beginning, the image is
converted into binary... | computer science |
24,575 | A Robust and Efficient Method for Improving Accuracy of License Plate
Characters Recognition | cs.CV | License Plate Recognition (LPR) plays an important role on the traffic
monitoring and parking management. A robust and efficient method for enhancing
accuracy of license plate characters recognition based on K Nearest Neighbours
(K-NN) classifier is presented in this paper. The system first prepares a
contour form of t... | computer science |
24,576 | Enhancing the Accuracy of Biometric Feature Extraction Fusion Using
Gabor Filter and Mahalanobis Distance Algorithm | cs.CV | Biometric recognition systems have advanced significantly in the last decade
and their use in specific applications will increase in the near future. The
ability to conduct meaningful comparisons and assessments will be crucial to
successful deployment and increasing biometric adoption. The best modality used
as unimod... | computer science |
24,577 | A unified framework for thermal face recognition | cs.CV | The reduction of the cost of infrared (IR) cameras in recent years has made
IR imaging a highly viable modality for face recognition in practice. A
particularly attractive advantage of IR-based over conventional, visible
spectrum-based face recognition stems from its invariance to visible
illumination. In this paper we... | computer science |
24,578 | A discussion on the validation tests employed to compare human action
recognition methods using the MSR Action3D dataset | cs.CV | This paper aims to determine which is the best human action recognition
method based on features extracted from RGB-D devices, such as the Microsoft
Kinect. A review of all the papers that make reference to MSR Action3D, the
most used dataset that includes depth information acquired from a RGB-D device,
has been perfor... | computer science |
24,579 | A Fast Hierarchical Method for Multi-script and Arbitrary Oriented Scene
Text Extraction | cs.CV | Typography and layout lead to the hierarchical organisation of text in words,
text lines, paragraphs. This inherent structure is a key property of text in
any script and language, which has nonetheless been minimally leveraged by
existing text detection methods. This paper addresses the problem of text
segmentation in ... | computer science |
24,580 | A Survey on Two Dimensional Cellular Automata and Its Application in
Image Processing | cs.CV | Parallel algorithms for solving any image processing task is a highly
demanded approach in the modern world. Cellular Automata (CA) are the most
common and simple models of parallel computation. So, CA has been successfully
used in the domain of image processing for the last couple of years. This paper
provides a surve... | computer science |
24,581 | Hyperspectral Imaging and Analysis for Sparse Reconstruction and
Recognition | cs.CV | This thesis proposes spatio-spectral techniques for hyperspectral image
analysis. Adaptive spatio-spectral support and variable exposure hyperspectral
imaging is demonstrated to improve spectral reflectance recovery from
hyperspectral images. Novel spectral dimensionality reduction techniques have
been proposed from th... | computer science |
24,582 | Clustering Approach Towards Image Segmentation: An Analytical Study | cs.CV | Image processing is an important research area in computer vision. Image
segmentation plays the vital rule in image processing research. There exist so
many methods for image segmentation. Clustering is an unsupervised study.
Clustering can also be used for image segmentation. In this paper, an in-depth
study is done o... | computer science |
24,583 | Merging and Shifting of Images with Prominence Coefficient for
Predictive Analysis using Combined Image | cs.CV | Shifting of objects in an image and merging many images after appropriate
shifting is being used in several engineering and scientific applications which
require complex perception development. A method has been presented here which
could be used in precision engineering and biological applications where more
precise p... | computer science |
24,584 | Accurate merging of images for predictive analysis using combined image | cs.CV | Several Scientific and engineering applications require merging of sampled
images for complex perception development. In most cases, for such
requirements, images are merged at intensity level. Even though it gives fairly
good perception of combined scenario of objects and scenes, it is found that
they are not sufficie... | computer science |
24,585 | A Bottom-Up Approach for Automatic Pancreas Segmentation in Abdominal CT
Scans | cs.CV | Organ segmentation is a prerequisite for a computer-aided diagnosis (CAD)
system to detect pathologies and perform quantitative analysis. For
anatomically high-variability abdominal organs such as the pancreas, previous
segmentation works report low accuracies when comparing to organs like the
heart or liver. In this p... | computer science |
24,586 | Sparse Coding on Symmetric Positive Definite Manifolds using Bregman
Divergences | cs.CV | This paper introduces sparse coding and dictionary learning for Symmetric
Positive Definite (SPD) matrices, which are often used in machine learning,
computer vision and related areas. Unlike traditional sparse coding schemes
that work in vector spaces, in this paper we discuss how SPD matrices can be
described by spar... | computer science |
24,587 | Kernel Coding: General Formulation and Special Cases | cs.CV | Representing images by compact codes has proven beneficial for many visual
recognition tasks. Most existing techniques, however, perform this coding step
directly in image feature space, where the distributions of the different
classes are typically entangled. In contrast, here, we study the problem of
performing codin... | computer science |
24,588 | Multi-tensor Completion for Estimating Missing Values in Video Data | cs.CV | Many tensor-based data completion methods aim to solve image and video
in-painting problems. But, all methods were only developed for a single
dataset. In most of real applications, we can usually obtain more than one
dataset to reflect one phenomenon, and all the datasets are mutually related in
some sense. Thus one q... | computer science |
24,589 | ImageNet Large Scale Visual Recognition Challenge | cs.CV | The ImageNet Large Scale Visual Recognition Challenge is a benchmark in
object category classification and detection on hundreds of object categories
and millions of images. The challenge has been run annually from 2010 to
present, attracting participation from more than fifty institutions.
This paper describes the c... | computer science |
24,590 | Transferring Landmark Annotations for Cross-Dataset Face Alignment | cs.CV | Dataset bias is a well known problem in object recognition domain. This
issue, nonetheless, is rarely explored in face alignment research. In this
study, we show that dataset plays an integral part of face alignment
performance. Specifically, owing to face alignment dataset bias, training on
one database and testing on... | computer science |
24,591 | Effective Spectral Unmixing via Robust Representation and Learning-based
Sparsity | cs.CV | Hyperspectral unmixing (HU) plays a fundamental role in a wide range of
hyperspectral applications. It is still challenging due to the common presence
of outlier channels and the large solution space. To address the above two
issues, we propose a novel model by emphasizing both robust representation and
learning-based ... | computer science |
24,592 | Action Recognition in the Frequency Domain | cs.CV | In this paper, we describe a simple strategy for mitigating variability in
temporal data series by shifting focus onto long-term, frequency domain
features that are less susceptible to variability. We apply this method to the
human action recognition task and demonstrate how working in the frequency
domain can yield go... | computer science |
24,593 | Visual Speech Recognition | cs.CV | Lip reading is used to understand or interpret speech without hearing it, a
technique especially mastered by people with hearing difficulties. The ability
to lip read enables a person with a hearing impairment to communicate with
others and to engage in social activities, which otherwise would be difficult.
Recent adva... | computer science |
24,594 | The Evolution of First Person Vision Methods: A Survey | cs.CV | The emergence of new wearable technologies such as action cameras and
smart-glasses has increased the interest of computer vision scientists in the
First Person perspective. Nowadays, this field is attracting attention and
investments of companies aiming to develop commercial devices with First Person
Vision recording ... | computer science |
24,595 | Very Deep Convolutional Networks for Large-Scale Image Recognition | cs.CV | In this work we investigate the effect of the convolutional network depth on
its accuracy in the large-scale image recognition setting. Our main
contribution is a thorough evaluation of networks of increasing depth using an
architecture with very small (3x3) convolution filters, which shows that a
significant improveme... | computer science |
24,596 | Identifying Synapses Using Deep and Wide Multiscale Recursive Networks | cs.CV | In this work, we propose a learning framework for identifying synapses using
a deep and wide multi-scale recursive (DAWMR) network, previously considered in
image segmentation applications. We apply this approach on electron microscopy
data from invertebrate fly brain tissue. By learning features directly from the
data... | computer science |
24,597 | Depth image hand tracking from an overhead perspective using partially
labeled, unbalanced data: Development and real-world testing | cs.CV | We present the development and evaluation of a hand tracking algorithm based
on single depth images captured from an overhead perspective for use in the
COACH prompting system. We train a random decision forest body part classifier
using approximately 5,000 manually labeled, unbalanced, partially labeled
training image... | computer science |
24,598 | A Computational Model of the Short-Cut Rule for 2D Shape Decomposition | cs.CV | We propose a new 2D shape decomposition method based on the short-cut rule.
The short-cut rule originates from cognition research, and states that the
human visual system prefers to partition an object into parts using the
shortest possible cuts. We propose and implement a computational model for the
short-cut rule and... | computer science |
24,599 | Image processing | cs.CV | Gabor filters can extract multi-orientation and multiscale features from face
images. Researchers have designed different ways to use the magnitude of the
filtered results for face recognition: Gabor Fisher classifier exploited only
the magnitude information of Gabor magnitude pictures (GMPs); Local Gabor
Binary Patter... | computer science |
24,600 | Comparing Feature Detectors: A bias in the repeatability criteria, and
how to correct it | cs.CV | Most computer vision application rely on algorithms finding local
correspondences between different images. These algorithms detect and compare
stable local invariant descriptors centered at scale-invariant keypoints.
Because of the importance of the problem, new keypoint detectors and
descriptors are constantly being ... | computer science |
24,601 | F-formation Detection: Individuating Free-standing Conversational Groups
in Images | cs.CV | Detection of groups of interacting people is a very interesting and useful
task in many modern technologies, with application fields spanning from
video-surveillance to social robotics. In this paper we first furnish a
rigorous definition of group considering the background of the social sciences:
this allows us to spe... | computer science |
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