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25,602 | Measurement of Road Traffic Parameters Based on Multi-Vehicle Tracking | cs.CV | Development of computing power and cheap video cameras enabled today's
traffic management systems to include more cameras and computer vision
applications for transportation system monitoring and control. Combined with
image processing algorithms cameras are used as sensors to measure road traffic
parameters like flow ... | computer science |
25,603 | You-Do, I-Learn: Unsupervised Multi-User egocentric Approach Towards
Video-Based Guidance | cs.CV | This paper presents an unsupervised approach towards automatically extracting
video-based guidance on object usage, from egocentric video and wearable gaze
tracking, collected from multiple users while performing tasks. The approach i)
discovers task relevant objects, ii) builds a model for each, iii)
distinguishes dif... | computer science |
25,604 | An Extension to Hough Transform Based on Gradient Orientation | cs.CV | The Hough transform is one of the most common methods for line detection. In
this paper we propose a novel extension of the regular Hough transform. The
proposed extension combines the extension of the accumulator space and the
local gradient orientation resulting in clutter reduction and yielding more
prominent peaks,... | computer science |
25,605 | No Spare Parts: Sharing Part Detectors for Image Categorization | cs.CV | This work aims for image categorization using a representation of distinctive
parts. Different from existing part-based work, we argue that parts are
naturally shared between image categories and should be modeled as such. We
motivate our approach with a quantitative and qualitative analysis by
backtracking where selec... | computer science |
25,606 | Integral Images: Efficient Algorithms for Their Computation and Storage
in Resource-Constrained Embedded Vision Systems | cs.CV | The integral image, an intermediate image representation, has found extensive
use in multi-scale local feature detection algorithms, such as Speeded-Up
Robust Features (SURF), allowing fast computation of rectangular features at
constant speed, independent of filter size. For resource-constrained real-time
embedded vis... | computer science |
25,607 | Memory-Efficient Design Strategy for a Parallel Embedded Integral Image
Computation Engine | cs.CV | In embedded vision systems, parallel computation of the integral image
presents several design challenges in terms of hardware resources, speed and
power consumption. Although recursive equations significantly reduce the number
of operations for computing the integral image, the required internal memory
becomes prohibi... | computer science |
25,608 | Rapid Online Analysis of Local Feature Detectors and Their
Complementarity | cs.CV | A vision system that can assess its own performance and take appropriate
actions online to maximize its effectiveness would be a step towards achieving
the long-cherished goal of imitating humans. This paper proposes a method for
performing an online performance analysis of local feature detectors, the
primary stage of... | computer science |
25,609 | Assessing The Performance Bounds Of Local Feature Detectors: Taking
Inspiration From Electronics Design Practices | cs.CV | Since local feature detection has been one of the most active research areas
in computer vision, a large number of detectors have been proposed. This has
rendered the task of characterizing the performance of various feature
detection methods an important issue in vision research. Inspired by the good
practices of elec... | computer science |
25,610 | Performance Characterization of Image Feature Detectors in Relation to
the Scene Content Utilizing a Large Image Database | cs.CV | Selecting the most suitable local invariant feature detector for a particular
application has rendered the task of evaluating feature detectors a critical
issue in vision research. No state-of-the-art image feature detector works
satisfactorily under all types of image transformations. Although the
literature offers a ... | computer science |
25,611 | Real-time Tracking Based on Neuromrophic Vision | cs.CV | Real-time tracking is an important problem in computer vision in which most
methods are based on the conventional cameras. Neuromorphic vision is a concept
defined by incorporating neuromorphic vision sensors such as silicon retinas in
vision processing system. With the development of the silicon technology,
asynchrono... | computer science |
25,612 | Color graph based wavelet transform with perceptual information | cs.CV | In this paper, we propose a numerical strategy to define a multiscale
analysis for color and multicomponent images based on the representation of
data on a graph. Our approach consists in computing the graph of an image using
the psychovisual information and analysing it by using the spectral graph
wavelet transform. W... | computer science |
25,613 | DeepSaliency: Multi-Task Deep Neural Network Model for Salient Object
Detection | cs.CV | A key problem in salient object detection is how to effectively model the
semantic properties of salient objects in a data-driven manner. In this paper,
we propose a multi-task deep saliency model based on a fully convolutional
neural network (FCNN) with global input (whole raw images) and global output
(whole saliency... | computer science |
25,614 | Sparse + Low Rank Decomposition of Annihilating Filter-based Hankel
Matrix for Impulse Noise Removal | cs.CV | Recently, so called annihilating filer-based low rank Hankel matrix (ALOHA)
approach was proposed as a powerful image inpainting method. Based on the
observation that smoothness or textures within an image patch corresponds to
sparse spectral components in the frequency domain, ALOHA exploits the
existence of annihilat... | computer science |
25,615 | Sequential Score Adaptation with Extreme Value Theory for Robust Railway
Track Inspection | cs.CV | Periodic inspections are necessary to keep railroad tracks in state of good
repair and prevent train accidents. Automatic track inspection using machine
vision technology has become a very effective inspection tool. Because of its
non-contact nature, this technology can be deployed on virtually any railway
vehicle to c... | computer science |
25,616 | Content adaptive screen image scaling | cs.CV | This paper proposes an efficient content adaptive screen image scaling scheme
for the real-time screen applications like remote desktop and screen sharing.
In the proposed screen scaling scheme, a screen content classification step is
first introduced to classify the screen image into text and pictorial regions.
Afterw... | computer science |
25,617 | Towards Direct Medical Image Analysis without Segmentation | cs.CV | Direct methods have recently emerged as an effective and efficient tool in
automated medical image analysis and become a trend to solve diverse
challenging tasks in clinical practise. Compared to traditional methods, direct
methods are of much more clinical significance by straightly targeting to the
final clinical goa... | computer science |
25,618 | Personalized Age Progression with Aging Dictionary | cs.CV | In this paper, we aim to automatically render aging faces in a personalized
way. Basically, a set of age-group specific dictionaries are learned, where the
dictionary bases corresponding to the same index yet from different
dictionaries form a particular aging process pattern cross different age
groups, and a linear co... | computer science |
25,619 | Modelling, Measuring and Compensating Color Weak Vision | cs.CV | We use methods from Riemann geometry to investigate transformations between
the color spaces of color-normal and color weak observers. The two main
applications are the simulation of the perception of a color weak observer for
a color normal observer and the compensation of color images in a way that a
color weak obser... | computer science |
25,620 | Efficient Unsupervised Temporal Segmentation of Motion Data | cs.CV | We introduce a method for automated temporal segmentation of human motion
data into distinct actions and compositing motion primitives based on
self-similar structures in the motion sequence. We use neighbourhood graphs for
the partitioning and the similarity information in the graph is further
exploited to cluster the... | computer science |
25,621 | Order-Fractal transition in abstract paintings | cs.CV | We report the degree of order of twenty-two Jackson Pollock's paintings using
\emph{Hausdorff-Besicovitch fractal dimension}. Through the maximum value of
each multi-fractal spectrum, the artworks are classify by the year in which
they were painted. It has been reported that Pollock's paintings are fractal
and it incre... | computer science |
25,622 | Semi-Automatic Segmentation of Autosomal Dominant Polycystic Kidneys
using Random Forests | cs.CV | This paper presents a method for 3D segmentation of kidneys from patients
with autosomal dominant polycystic kidney disease (ADPKD) and severe renal
insufficiency, using computed tomography (CT) data. ADPKD severely alters the
shape of the kidneys due to non-uniform formation of cysts. As a consequence,
fully automatic... | computer science |
25,623 | Objects2action: Classifying and localizing actions without any video
example | cs.CV | The goal of this paper is to recognize actions in video without the need for
examples. Different from traditional zero-shot approaches we do not demand the
design and specification of attribute classifiers and class-to-attribute
mappings to allow for transfer from seen classes to unseen classes. Our key
contribution is... | computer science |
25,624 | Predicting Performance of a Face Recognition System Based on Image
Quality | cs.CV | In this dissertation, we present a generative model to capture the relation
between facial image quality features (like pose, illumination direction, etc)
and face recognition performance. Such a model can be used to predict the
performance of a face recognition system. Since the model is based solely on
image quality ... | computer science |
25,625 | Predicting Face Recognition Performance Using Image Quality | cs.CV | This paper proposes a data driven model to predict the performance of a face
recognition system based on image quality features. We model the relationship
between image quality features (e.g. pose, illumination, etc.) and recognition
performance measures using a probability density function. To address the issue
of lim... | computer science |
25,626 | Image Parsing with a Wide Range of Classes and Scene-Level Context | cs.CV | This paper presents a nonparametric scene parsing approach that improves the
overall accuracy, as well as the coverage of foreground classes in scene
images. We first improve the label likelihood estimates at superpixels by
merging likelihood scores from different probabilistic classifiers. This boosts
the classificati... | computer science |
25,627 | Computational models of attention | cs.CV | This chapter reviews recent computational models of visual attention. We
begin with models for the bottom-up or stimulus-driven guidance of attention to
salient visual items, which we examine in seven different broad categories. We
then examine more complex models which address the top-down or goal-oriented
guidance of... | computer science |
25,628 | Depth Extraction from Videos Using Geometric Context and Occlusion
Boundaries | cs.CV | We present an algorithm to estimate depth in dynamic video scenes. We propose
to learn and infer depth in videos from appearance, motion, occlusion
boundaries, and geometric context of the scene. Using our method, depth can be
estimated from unconstrained videos with no requirement of camera pose
estimation, and with s... | computer science |
25,629 | Geometric Context from Videos | cs.CV | We present a novel algorithm for estimating the broad 3D geometric structure
of outdoor video scenes. Leveraging spatio-temporal video segmentation, we
decompose a dynamic scene captured by a video into geometric classes, based on
predictions made by region-classifiers that are trained on appearance and
motion features... | computer science |
25,630 | Finding Temporally Consistent Occlusion Boundaries in Videos using
Geometric Context | cs.CV | We present an algorithm for finding temporally consistent occlusion
boundaries in videos to support segmentation of dynamic scenes. We learn
occlusion boundaries in a pairwise Markov random field (MRF) framework. We
first estimate the probability of an spatio-temporal edge being an occlusion
boundary by using appearanc... | computer science |
25,631 | Vehicle Color Recognition using Convolutional Neural Network | cs.CV | Vehicle color information is one of the important elements in ITS
(Intelligent Traffic System). In this paper, we present a vehicle color
recognition method using convolutional neural network (CNN). Naturally, CNN is
designed to learn classification method based on shape information, but we
proved that CNN can also lea... | computer science |
25,632 | A Markov Random Field and Active Contour Image Segmentation Model for
Animal Spots Patterns | cs.CV | Non-intrusive biometrics of animals using images allows to analyze phenotypic
populations and individuals with patterns like stripes and spots without
affecting the studied subjects. However, non-intrusive biometrics demand a well
trained subject or the development of computer vision algorithms that ease the
identifica... | computer science |
25,633 | Aggregating Deep Convolutional Features for Image Retrieval | cs.CV | Several recent works have shown that image descriptors produced by deep
convolutional neural networks provide state-of-the-art performance for image
classification and retrieval problems. It has also been shown that the
activations from the convolutional layers can be interpreted as local features
describing particular... | computer science |
25,634 | Video Paragraph Captioning Using Hierarchical Recurrent Neural Networks | cs.CV | We present an approach that exploits hierarchical Recurrent Neural Networks
(RNNs) to tackle the video captioning problem, i.e., generating one or multiple
sentences to describe a realistic video. Our hierarchical framework contains a
sentence generator and a paragraph generator. The sentence generator produces
one sim... | computer science |
25,635 | Computational models: Bottom-up and top-down aspects | cs.CV | Computational models of visual attention have become popular over the past
decade, we believe primarily for two reasons: First, models make testable
predictions that can be explored by experimentalists as well as theoreticians,
second, models have practical and technological applications of interest to the
applied scie... | computer science |
25,636 | Some like it hot - visual guidance for preference prediction | cs.CV | For people first impressions of someone are of determining importance. They
are hard to alter through further information. This begs the question if a
computer can reach the same judgement. Earlier research has already pointed out
that age, gender, and average attractiveness can be estimated with reasonable
precision. ... | computer science |
25,637 | Defect Detection Techniques for Airbag Production Sewing Stages | cs.CV | Airbags are subject to strict quality control in order to ensure passengers
safety. The quality of fabric and sewing thread influence the final product and
therefore, sewing defects must be early and accurately detected, in order to
remove the item from production. Airbag seams assembly can take various forms,
using li... | computer science |
25,638 | Learning Multi-Domain Convolutional Neural Networks for Visual Tracking | cs.CV | We propose a novel visual tracking algorithm based on the representations
from a discriminatively trained Convolutional Neural Network (CNN). Our
algorithm pretrains a CNN using a large set of videos with tracking
ground-truths to obtain a generic target representation. Our network is
composed of shared layers and mult... | computer science |
25,639 | ENFT: Efficient Non-Consecutive Feature Tracking for Robust
Structure-from-Motion | cs.CV | Structure-from-motion (SfM) largely relies on feature tracking. In image
sequences, if disjointed tracks caused by objects moving in and out of the
field of view, occasional occlusion, or image noise, are not handled well,
corresponding SfM could be affected. This problem becomes severer for
large-scale scenes, which t... | computer science |
25,640 | Hybrid One-Shot 3D Hand Pose Estimation by Exploiting Uncertainties | cs.CV | Model-based approaches to 3D hand tracking have been shown to perform well in
a wide range of scenarios. However, they require initialisation and cannot
recover easily from tracking failures that occur due to fast hand motions.
Data-driven approaches, on the other hand, can quickly deliver a solution, but
the results o... | computer science |
25,641 | Scale-aware Fast R-CNN for Pedestrian Detection | cs.CV | In this work, we consider the problem of pedestrian detection in natural
scenes. Intuitively, instances of pedestrians with different spatial scales may
exhibit dramatically different features. Thus, large variance in instance
scales, which results in undesirable large intra-category variance in features,
may severely ... | computer science |
25,642 | VISALOGY: Answering Visual Analogy Questions | cs.CV | In this paper, we study the problem of answering visual analogy questions.
These questions take the form of image A is to image B as image C is to what.
Answering these questions entails discovering the mapping from image A to image
B and then extending the mapping to image C and searching for the image D such
that the... | computer science |
25,643 | Postprocessing of Compressed Images via Sequential Denoising | cs.CV | In this work we propose a novel postprocessing technique for
compression-artifact reduction. Our approach is based on posing this task as an
inverse problem, with a regularization that leverages on existing
state-of-the-art image denoising algorithms. We rely on the recently proposed
Plug-and-Play Prior framework, sugg... | computer science |
25,644 | Deep Recurrent Regression for Facial Landmark Detection | cs.CV | We propose a novel end-to-end deep architecture for face landmark detection,
based on a deep convolutional and deconvolutional network followed by carefully
designed recurrent network structures. The pipeline of this architecture
consists of three parts. Through the first part, we encode an input face image
to resoluti... | computer science |
25,645 | Estimating Target Signatures with Diverse Density | cs.CV | Hyperspectral target detection algorithms rely on knowing the desired target
signature in advance. However, obtaining an effective target signature can be
difficult; signatures obtained from laboratory measurements or
hand-spectrometers in the field may not transfer to airborne imagery
effectively. One approach to deal... | computer science |
25,646 | Bioinspired Visual Motion Estimation | cs.CV | Visual motion estimation is a computationally intensive, but important task
for sighted animals. Replicating the robustness and efficiency of biological
visual motion estimation in artificial systems would significantly enhance the
capabilities of future robotic agents. 25 years ago, in this very journal,
Carver Mead o... | computer science |
25,647 | Semantic Cross-View Matching | cs.CV | Matching cross-view images is challenging because the appearance and
viewpoints are significantly different. While low-level features based on
gradient orientations or filter responses can drastically vary with such
changes in viewpoint, semantic information of images however shows an invariant
characteristic in this r... | computer science |
25,648 | Fast Neuromimetic Object Recognition using FPGA Outperforms GPU
Implementations | cs.CV | Recognition of objects in still images has traditionally been regarded as a
difficult computational problem. Although modern automated methods for visual
object recognition have achieved steadily increasing recognition accuracy, even
the most advanced computational vision approaches are unable to obtain
performance equ... | computer science |
25,649 | Regional Active Contours based on Variational level sets and Machine
Learning for Image Segmentation | cs.CV | Image segmentation is the problem of partitioning an image into different
subsets, where each subset may have a different characterization in terms of
color, intensity, texture, and/or other features. Segmentation is a fundamental
component of image processing, and plays a significant role in computer vision,
object re... | computer science |
25,650 | FireCaffe: near-linear acceleration of deep neural network training on
compute clusters | cs.CV | Long training times for high-accuracy deep neural networks (DNNs) impede
research into new DNN architectures and slow the development of high-accuracy
DNNs. In this paper we present FireCaffe, which successfully scales deep neural
network training across a cluster of GPUs. We also present a number of best
practices to ... | computer science |
25,651 | Towards Reading Hidden Emotions: A comparative Study of Spontaneous
Micro-expression Spotting and Recognition Methods | cs.CV | Micro-expressions (MEs) are rapid, involuntary facial expressions which
reveal emotions that people do not intend to show. Studying MEs is valuable as
recognizing them has many important applications, particularly in forensic
science and psychotherapy. However, analyzing spontaneous MEs is very
challenging due to their... | computer science |
25,652 | Semantic Summarization of Egocentric Photo Stream Events | cs.CV | With the rapid increase of users of wearable cameras in recent years and of
the amount of data they produce, there is a strong need for automatic retrieval
and summarization techniques. This work addresses the problem of automatically
summarizing egocentric photo streams captured through a wearable camera by
taking an ... | computer science |
25,653 | Circle detection using isosceles triangles sampling | cs.CV | Detection of circular objects in digital images is an important problem in
several vision applications. Circle detection using randomized sampling has
been developed in recent years to reduce the computational intensity.
Randomized sampling, however, is sensitive to noise that can lead to reduced
accuracy and false-pos... | computer science |
25,654 | Water Detection through Spatio-Temporal Invariant Descriptors | cs.CV | In this work, we aim to segment and detect water in videos. Water detection
is beneficial for appllications such as video search, outdoor surveillance, and
systems such as unmanned ground vehicles and unmanned aerial vehicles. The
specific problem, however, is less discussed compared to general texture
recognition. Her... | computer science |
25,655 | Pixel-wise Segmentation of Street with Neural Networks | cs.CV | Pixel-wise street segmentation of photographs taken from a drivers
perspective is important for self-driving cars and can also support other
object recognition tasks. A framework called SST was developed to examine the
accuracy and execution time of different neural networks. The best neural
network achieved an $F_1$-s... | computer science |
25,656 | Color Space Transformation Network | cs.CV | Deep networks have become very popular over the past few years. The main
reason for this widespread use is their excellent ability to learn and predict
knowledge in a very easy and efficient way. Convolutional neural networks and
auto-encoders have become the normal in the area of imaging and computer vision
achieving ... | computer science |
25,657 | Robust Registration of Calcium Images by Learned Contrast Synthesis | cs.CV | Multi-modal image registration is a challenging task that is vital to fuse
complementary signals for subsequent analyses. Despite much research into cost
functions addressing this challenge, there exist cases in which these are
ineffective. In this work, we show that (1) this is true for the registration
of in-vivo Dro... | computer science |
25,658 | Robust Large-Scale Localization in 3D Point Clouds Revisited | cs.CV | We tackle the problem of getting a full 6-DOF pose estimation of a query
image inside a given point cloud. This technical report re-evaluates the
algorithms proposed by Y. Li et al. "Worldwide Pose Estimation using 3D Point
Cloud". Our code computes poses from 3 or 4 points, with both known and unknown
focal length. Th... | computer science |
25,659 | Image-Based Correction of Continuous and Discontinuous Non-Planar Axial
Distortion in Serial Section Microscopy | cs.CV | Motivation: Serial section microscopy is an established method for detailed
anatomy reconstruction of biological specimen. During the last decade, high
resolution electron microscopy (EM) of serial sections has become the de-facto
standard for reconstruction of neural connectivity at ever increasing scales
(EM connecto... | computer science |
25,660 | Cell identification in whole-brain multiview images of neural activation | cs.CV | We present a scalable method for brain cell identification in multiview
confocal light sheet microscopy images. Our algorithmic pipeline includes a
hierarchical registration approach and a novel multiview version of semantic
deconvolution that simultaneously enhance visibility of fluorescent cell
bodies, equalize their... | computer science |
25,661 | Face Aging Effect Simulation using Hidden Factor Analysis Joint Sparse
Representation | cs.CV | Face aging simulation has received rising investigations nowadays, whereas it
still remains a challenge to generate convincing and natural age-progressed
face images. In this paper, we present a novel approach to such an issue by
using hidden factor analysis joint sparse representation. In contrast to the
majority of t... | computer science |
25,662 | Decomposition into Low-rank plus Additive Matrices for
Background/Foreground Separation: A Review for a Comparative Evaluation with
a Large-Scale Dataset | cs.CV | Recent research on problem formulations based on decomposition into low-rank
plus sparse matrices shows a suitable framework to separate moving objects from
the background. The most representative problem formulation is the Robust
Principal Component Analysis (RPCA) solved via Principal Component Pursuit
(PCP) which de... | computer science |
25,663 | Towards a tracking algorithm based on the clustering of spatio-temporal
clouds of points | cs.CV | The interest in 3D dynamical tracking is growing in fields such as robotics,
biology and fluid dynamics. Recently, a major source of progress in 3D tracking
has been the study of collective behaviour in biological systems, where the
trajectories of individual animals moving within large and dense groups need to
be reco... | computer science |
25,664 | Enhancing Feature Tracking With Gyro Regularization | cs.CV | We present a deeply integrated method of exploiting low-cost gyroscopes to
improve general purpose feature tracking. Most previous methods use gyroscopes
to initialize and bound the search for features. In contrast, we use them to
regularize the tracking energy function so that they can directly assist in the
tracking ... | computer science |
25,665 | Coherent Motion Segmentation in Moving Camera Videos using Optical Flow
Orientations | cs.CV | In moving camera videos, motion segmentation is commonly performed using the
image plane motion of pixels, or optical flow. However, objects that are at
different depths from the camera can exhibit different optical flows even if
they share the same real-world motion. This can cause a depth-dependent
segmentation of th... | computer science |
25,666 | Background subtraction - separating the modeling and the inference | cs.CV | In its early implementations, background modeling was a process of building a
model for the background of a video with a stationary camera, and identifying
pixels that did not conform well to this model. The pixels that were not
well-described by the background model were assumed to be moving objects. Many
systems toda... | computer science |
25,667 | Background Modeling Using Adaptive Pixelwise Kernel Variances in a
Hybrid Feature Space | cs.CV | Recent work on background subtraction has shown developments on two major
fronts. In one, there has been increasing sophistication of probabilistic
models, from mixtures of Gaussians at each pixel [7], to kernel density
estimates at each pixel [1], and more recently to joint domainrange density
estimates that incorpora... | computer science |
25,668 | Image classification based on support vector machine and the fusion of
complementary features | cs.CV | Image Classification based on BOW (Bag-of-words) has broad application
prospect in pattern recognition field but the shortcomings are existed because
of single feature and low classification accuracy. To this end we combine three
ingredients: (i) Three features with functions of mutual complementation are
adopted to de... | computer science |
25,669 | Multi-Target Tracking and Occlusion Handling with Learned Variational
Bayesian Clusters and a Social Force Model | cs.CV | This paper considers the problem of multiple human target tracking in a
sequence of video data. A solution is proposed which is able to deal with the
challenges of a varying number of targets, interactions and when every target
gives rise to multiple measurements. The developed novel algorithm comprises
variational Bay... | computer science |
25,670 | Wood Species Recognition Based on SIFT Keypoint Histogram | cs.CV | Traditionally, only experts who are equipped with professional knowledge and
rich experience are able to recognize different species of wood. Applying image
processing techniques for wood species recognition can not only reduce the
expense to train qualified identifiers, but also increase the recognition
accuracy. In t... | computer science |
25,671 | Radon-Nikodym approximation in application to image analysis | cs.CV | For an image pixel information can be converted to the moments of some basis
$Q_k$, e.g. Fourier-Mellin, Zernike, monomials, etc. Given sufficient number of
moments pixel information can be completely recovered, for insufficient number
of moments only partial information can be recovered and the image
reconstruction is... | computer science |
25,672 | Recovering hard-to-find object instances by sampling context-based
object proposals | cs.CV | In this paper we focus on improving object detection performance in terms of
recall. We propose a post-detection stage during which we explore the image
with the objective of recovering missed detections. This exploration is
performed by sampling object proposals in the image. We analyze four different
strategies to pe... | computer science |
25,673 | Facial Expression Recognition Using Sparse Gaussian Conditional Random
Field | cs.CV | The analysis of expression and facial Action Units (AUs) detection are very
important tasks in fields of computer vision and Human Computer Interaction
(HCI) due to the wide range of applications in human life. Many works has been
done during the past few years which has their own advantages and
disadvantages. In this ... | computer science |
25,674 | Pooling the Convolutional Layers in Deep ConvNets for Action Recognition | cs.CV | Deep ConvNets have shown its good performance in image classification tasks.
However it still remains as a problem in deep video representation for action
recognition. The problem comes from two aspects: on one hand, current video
ConvNets are relatively shallow compared with image ConvNets, which limits its
capability... | computer science |
25,675 | Seven ways to improve example-based single image super resolution | cs.CV | In this paper we present seven techniques that everybody should know to
improve example-based single image super resolution (SR): 1) augmentation of
data, 2) use of large dictionaries with efficient search structures, 3)
cascading, 4) image self-similarities, 5) back projection refinement, 6)
enhanced prediction by con... | computer science |
25,676 | Learning Visual Features from Large Weakly Supervised Data | cs.CV | Convolutional networks trained on large supervised dataset produce visual
features which form the basis for the state-of-the-art in many computer-vision
problems. Further improvements of these visual features will likely require
even larger manually labeled data sets, which severely limits the pace at which
progress ca... | computer science |
25,677 | Fingertip in the Eye: A cascaded CNN pipeline for the real-time
fingertip detection in egocentric videos | cs.CV | We introduce a new pipeline for hand localization and fingertip detection.
For RGB images captured from an egocentric vision mobile camera, hand and
fingertip detection remains a challenging problem due to factors like
background complexity and hand shape variety. To address these issues
accurately and robustly, we bui... | computer science |
25,678 | Deep Sliding Shapes for Amodal 3D Object Detection in RGB-D Images | cs.CV | We focus on the task of amodal 3D object detection in RGB-D images, which
aims to produce a 3D bounding box of an object in metric form at its full
extent. We introduce Deep Sliding Shapes, a 3D ConvNet formulation that takes a
3D volumetric scene from a RGB-D image as input and outputs 3D object bounding
boxes. In our... | computer science |
25,679 | Review of Person Re-identification Techniques | cs.CV | Person re-identification across different surveillance cameras with disjoint
fields of view has become one of the most interesting and challenging subjects
in the area of intelligent video surveillance. Although several methods have
been developed and proposed, certain limitations and unresolved issues remain.
In all o... | computer science |
25,680 | A Survey of the Trends in Facial and Expression Recognition Databases
and Methods | cs.CV | Automated facial identification and facial expression recognition have been
topics of active research over the past few decades. Facial and expression
recognition find applications in human-computer interfaces, subject tracking,
real-time security surveillance systems and social networking. Several holistic
and geometr... | computer science |
25,681 | SCUT-FBP: A Benchmark Dataset for Facial Beauty Perception | cs.CV | In this paper, a novel face dataset with attractiveness ratings, namely, the
SCUT-FBP dataset, is developed for automatic facial beauty perception. This
dataset provides a benchmark to evaluate the performance of different methods
for facial attractiveness prediction, including the state-of-the-art deep
learning method... | computer science |
25,682 | LOGO-Net: Large-scale Deep Logo Detection and Brand Recognition with
Deep Region-based Convolutional Networks | cs.CV | Logo detection from images has many applications, particularly for brand
recognition and intellectual property protection. Most existing studies for
logo recognition and detection are based on small-scale datasets which are not
comprehensive enough when exploring emerging deep learning techniques. In this
paper, we int... | computer science |
25,683 | A new humanlike facial attractiveness predictor with cascaded
fine-tuning deep learning model | cs.CV | This paper proposes a deep leaning method to address the challenging facial
attractiveness prediction problem. The method constructs a convolutional neural
network of facial beauty prediction using a new deep cascaded fine-turning
scheme with various face inputting channels, such as the original RGB face
image, the det... | computer science |
25,684 | A Century of Portraits: A Visual Historical Record of American High
School Yearbooks | cs.CV | Many details about our world are not captured in written records because they
are too mundane or too abstract to describe in words. Fortunately, since the
invention of the camera, an ever-increasing number of photographs capture much
of this otherwise lost information. This plethora of artifacts documenting our
"visual... | computer science |
25,685 | Semantic Segmentation with Boundary Neural Fields | cs.CV | The state-of-the-art in semantic segmentation is currently represented by
fully convolutional networks (FCNs). However, FCNs use large receptive fields
and many pooling layers, both of which cause blurring and low spatial
resolution in the deep layers. As a result FCNs tend to produce segmentations
that are poorly loca... | computer science |
25,686 | Exploiting Egocentric Object Prior for 3D Saliency Detection | cs.CV | On a minute-to-minute basis people undergo numerous fluid interactions with
objects that barely register on a conscious level. Recent neuroscientific
research demonstrates that humans have a fixed size prior for salient objects.
This suggests that a salient object in 3D undergoes a consistent transformation
such that p... | computer science |
25,687 | A Light CNN for Deep Face Representation with Noisy Labels | cs.CV | Convolution neural network (CNN) has significantly pushed forward the
development of face recognition and analysis techniques. Current CNN models
tend to be deeper and larger to better fit large amounts of training data. When
training data are from internet, their labels are often ambiguous and
inaccurate. This paper p... | computer science |
25,688 | Weakly Supervised Deep Detection Networks | cs.CV | Weakly supervised learning of object detection is an important problem in
image understanding that still does not have a satisfactory solution. In this
paper, we address this problem by exploiting the power of deep convolutional
neural networks pre-trained on large-scale image-level classification tasks. We
propose a w... | computer science |
25,689 | Spatially Coherent Random Forests | cs.CV | Spatially Coherent Random Forest (SCRF) extends Random Forest to create
spatially coherent labeling. Each split function in SCRF is evaluated based on
a traditional information gain measure that is regularized by a spatial
coherency term. This way, SCRF is encouraged to choose split functions that
cluster pixels both i... | computer science |
25,690 | Massive Online Crowdsourced Study of Subjective and Objective Picture
Quality | cs.CV | Most publicly available image quality databases have been created under
highly controlled conditions by introducing graded simulated distortions onto
high-quality photographs. However, images captured using typical real-world
mobile camera devices are usually afflicted by complex mixtures of multiple
distortions, which... | computer science |
25,691 | Hyperspectral Image Recovery via Hybrid Regularization | cs.CV | Natural images tend to mostly consist of smooth regions with individual
pixels having highly correlated spectra. This information can be exploited to
recover hyperspectral images of natural scenes from their incomplete and noisy
measurements. To perform the recovery while taking full advantage of the prior
knowledge, w... | computer science |
25,692 | Traffic Sign Classification Using Deep Inception Based Convolutional
Networks | cs.CV | In this work, we propose a novel deep network for traffic sign classification
that achieves outstanding performance on GTSRB surpassing all previous methods.
Our deep network consists of spatial transformer layers and a modified version
of inception module specifically designed for capturing local and global
features t... | computer science |
25,693 | Improvised Salient Object Detection and Manipulation | cs.CV | In case of salient subject recognition, computer algorithms have been heavily
relied on scanning of images from top-left to bottom-right systematically and
apply brute-force when attempting to locate objects of interest. Thus, the
process turns out to be quite time consuming. Here a novel approach and a
simple solution... | computer science |
25,694 | Deep Representation of Facial Geometric and Photometric Attributes for
Automatic 3D Facial Expression Recognition | cs.CV | In this paper, we present a novel approach to automatic 3D Facial Expression
Recognition (FER) based on deep representation of facial 3D geometric and 2D
photometric attributes. A 3D face is firstly represented by its geometric and
photometric attributes, including the geometry map, normal maps, normalized
curvature ma... | computer science |
25,695 | 3D Time-lapse Reconstruction from Internet Photos | cs.CV | Given an Internet photo collection of a landmark, we compute a 3D time-lapse
video sequence where a virtual camera moves continuously in time and space.
While previous work assumed a static camera, the addition of camera motion
during the time-lapse creates a very compelling impression of parallax.
Achieving this goal,... | computer science |
25,696 | Online Action Recognition based on Incremental Learning of Weighted
Covariance Descriptors | cs.CV | Different from traditional action recognition based on video segments, online
action recognition aims to recognize actions from unsegmented streams of data
in a continuous manner. One way for online recognition is based on the evidence
accumulation over time to make predictions from stream videos. This paper
presents a... | computer science |
25,697 | Analyzing Stability of Convolutional Neural Networks in the Frequency
Domain | cs.CV | Understanding the internal process of ConvNets is commonly done using
visualization techniques. However, these techniques do not usually provide a
tool for estimating the stability of a ConvNet against noise. In this paper, we
show how to analyze a ConvNet in the frequency domain using a 4-dimensional
visualization tec... | computer science |
25,698 | Dynamic Belief Fusion for Object Detection | cs.CV | A novel approach for the fusion of heterogeneous object detection methods is
proposed. In order to effectively integrate the outputs of multiple detectors,
the level of ambiguity in each individual detection score is estimated using
the precision/recall relationship of the corresponding detector. The main
contribution ... | computer science |
25,699 | The Radon cumulative distribution transform and its application to image
classification | cs.CV | Invertible image representation methods (transforms) are routinely employed
as low-level image processing operations based on which feature extraction and
recognition algorithms are developed. Most transforms in current use (e.g.
Fourier, Wavelet, etc.) are linear transforms, and, by themselves, are unable
to substanti... | computer science |
25,700 | Semantic Instance Annotation of Street Scenes by 3D to 2D Label Transfer | cs.CV | Semantic annotations are vital for training models for object recognition,
semantic segmentation or scene understanding. Unfortunately, pixelwise
annotation of images at very large scale is labor-intensive and only little
labeled data is available, particularly at instance level and for street
scenes. In this paper, we... | computer science |
25,701 | TemplateNet for Depth-Based Object Instance Recognition | cs.CV | We present a novel deep architecture termed templateNet for depth based
object instance recognition. Using an intermediate template layer we exploit
prior knowledge of an object's shape to sparsify the feature maps. This has
three advantages: (i) the network is better regularised resulting in structured
filters; (ii) t... | computer science |
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