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25,202 | Subsampled terahertz data reconstruction based on spatio-temporal
dictionary learning | cs.CV | In this paper, the problem of terahertz pulsed imaging and reconstruction is
addressed. It is assumed that an incomplete (subsampled) three dimensional THz
data set has been acquired and the aim is to recover all missing samples. A
sparsity-inducing approach is proposed for this purpose. First, a simple
interpolation i... | computer science |
25,203 | Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation | cs.CV | We propose a novel deep neural network architecture for semi-supervised
semantic segmentation using heterogeneous annotations. Contrary to existing
approaches posing semantic segmentation as a single task of region-based
classification, our algorithm decouples classification and segmentation, and
learns a separate netw... | computer science |
25,204 | Histopathological Image Classification using Discriminative
Feature-oriented Dictionary Learning | cs.CV | In histopathological image analysis, feature extraction for classification is
a challenging task due to the diversity of histology features suitable for each
problem as well as presence of rich geometrical structures. In this paper, we
propose an automatic feature discovery framework via learning class-specific
diction... | computer science |
25,205 | Depth Perception in Autostereograms: 1/f-Noise is Best | cs.CV | An autostereogram is a single image that encodes depth information that pops
out when looking at it. The trick is achieved by replicating a vertical strip
that sets a basic two-dimensional pattern with disparity shifts that encode a
three-dimensional scene. It is of interest to explore the dependency between
the ease o... | computer science |
25,206 | Extract an essential skeleton of a character as a graph from a character
image | cs.CV | This paper aims to make a graph representing an essential skeleton of a
character from an image that includes a machine printed or a handwritten
character using the growing neural gas (GNG) method and the relative
neighborhood graph (RNG) algorithm. The visual system in our brain can
recognize printed characters and ha... | computer science |
25,207 | Robust High Quality Image Guided Depth Upsampling | cs.CV | Time-of-Flight (ToF) depth sensing camera is able to obtain depth maps at a
high frame rate. However, its low resolution and sensitivity to the noise are
always a concern. A popular solution is upsampling the obtained noisy low
resolution depth map with the guidance of the companion high resolution color
image. However... | computer science |
25,208 | A Discriminative Representation of Convolutional Features for Indoor
Scene Recognition | cs.CV | Indoor scene recognition is a multi-faceted and challenging problem due to
the diverse intra-class variations and the confusing inter-class similarities.
This paper presents a novel approach which exploits rich mid-level
convolutional features to categorize indoor scenes. Traditionally used
convolutional features prese... | computer science |
25,209 | CFORB: Circular FREAK-ORB Visual Odometry | cs.CV | We present a novel Visual Odometry algorithm entitled Circular FREAK-ORB
(CFORB). This algorithm detects features using the well-known ORB algorithm
[12] and computes feature descriptors using the FREAK algorithm [14]. CFORB is
invariant to both rotation and scale changes, and is suitable for use in
environments with u... | computer science |
25,210 | Partial Functional Correspondence | cs.CV | In this paper, we propose a method for computing partial functional
correspondence between non-rigid shapes. We use perturbation analysis to show
how removal of shape parts changes the Laplace-Beltrami eigenfunctions, and
exploit it as a prior on the spectral representation of the correspondence.
Corresponding parts ar... | computer science |
25,211 | A Spatial Layout and Scale Invariant Feature Representation for Indoor
Scene Classification | cs.CV | Unlike standard object classification, where the image to be classified
contains one or multiple instances of the same object, indoor scene
classification is quite different since the image consists of multiple distinct
objects. Further, these objects can be of varying sizes and are present across
numerous spatial loca... | computer science |
25,212 | Deep Generative Image Models using a Laplacian Pyramid of Adversarial
Networks | cs.CV | In this paper we introduce a generative parametric model capable of producing
high quality samples of natural images. Our approach uses a cascade of
convolutional networks within a Laplacian pyramid framework to generate images
in a coarse-to-fine fashion. At each level of the pyramid, a separate
generative convnet mod... | computer science |
25,213 | To Know Where We Are: Vision-Based Positioning in Outdoor Environments | cs.CV | Augmented reality (AR) displays become more and more popular recently,
because of its high intuitiveness for humans and high-quality head-mounted
display have rapidly developed. To achieve such displays with augmented
information, highly accurate image registration or ego-positioning are
required, but little attention ... | computer science |
25,214 | New Descriptor for Glomerulus Detection in Kidney Microscopy Image | cs.CV | Glomerulus detection is a key step in histopathological evaluation of
microscopy images of kidneys. However, the task of automatic detection of
glomeruli poses challenges due to the disparity in sizes and shapes of
glomeruli in renal sections. Moreover, extensive variations of their
intensities due to heterogeneity in ... | computer science |
25,215 | Exploring the influence of scale on artist attribution | cs.CV | Previous work has shown that the artist of an artwork can be identified by
use of computational methods that analyse digital images. However, the
digitised artworks are often investigated at a coarse scale discarding many of
the important details that may define an artist's style. In recent years high
resolution images... | computer science |
25,216 | Scene-adaptive Coded Apertures Imaging | cs.CV | Coded aperture imaging systems have recently shown great success in
recovering scene depth and extending the depth-of-field. The ideal pattern,
however, would have to serve two conflicting purposes: 1) be broadband to
ensure robust deconvolution and 2) has sufficient zero-crossings for a high
depth discrepancy. This pa... | computer science |
25,217 | Stereoscopic Cinema | cs.CV | Stereoscopic cinema has seen a surge of activity in recent years, and for the
first time all of the major Hollywood studios released 3-D movies in 2009. This
is happening alongside the adoption of 3-D technology for sports broadcasting,
and the arrival of 3-D TVs for the home. Two previous attempts to introduce 3-D
cin... | computer science |
25,218 | Crowd Flow Segmentation in Compressed Domain using CRF | cs.CV | Crowd flow segmentation is an important step in many video surveillance
tasks. In this work, we propose an algorithm for segmenting flows in H.264
compressed videos in a completely unsupervised manner. Our algorithm works on
motion vectors which can be obtained by partially decoding the compressed video
without extract... | computer science |
25,219 | moco: Fast Motion Correction for Calcium Imaging | cs.CV | Motion correction is the first in a pipeline of algorithms to analyze calcium
imaging videos and extract biologically relevant information, for example the
network structure of the neurons therein. Fast motion correction would be
especially critical for closed-loop activity triggered stimulation experiments,
where accu... | computer science |
25,220 | Learning to Segment Object Candidates | cs.CV | Recent object detection systems rely on two critical steps: (1) a set of
object proposals is predicted as efficiently as possible, and (2) this set of
candidate proposals is then passed to an object classifier. Such approaches
have been shown they can be fast, while achieving the state of the art in
detection performan... | computer science |
25,221 | 3D Reconstruction from Full-view Fisheye Camera | cs.CV | In this report, we proposed a 3D reconstruction method for the full-view
fisheye camera. The camera we used is Ricoh Theta, which captures spherical
images and has a wide field of view (FOV). The conventional stereo apporach
based on perspective camera model cannot be directly applied and instead we
used a spherical ca... | computer science |
25,222 | Filtrated Algebraic Subspace Clustering | cs.CV | Subspace clustering is the problem of clustering data that lie close to a
union of linear subspaces. In the abstract form of the problem, where no noise
or other corruptions are present, the data are assumed to lie in general
position inside the algebraic variety of a union of subspaces, and the
objective is to decompo... | computer science |
25,223 | Mining Mid-level Visual Patterns with Deep CNN Activations | cs.CV | The purpose of mid-level visual element discovery is to find clusters of
image patches that are both representative and discriminative. Here we study
this problem from the prospective of pattern mining while relying on the
recently popularized Convolutional Neural Networks (CNNs). We observe that a
fully-connected CNN ... | computer science |
25,224 | DeepOrgan: Multi-level Deep Convolutional Networks for Automated
Pancreas Segmentation | cs.CV | Automatic organ segmentation is an important yet challenging problem for
medical image analysis. The pancreas is an abdominal organ with very high
anatomical variability. This inhibits previous segmentation methods from
achieving high accuracies, especially compared to other organs such as the
liver, heart or kidneys. ... | computer science |
25,225 | Target Tracking In Real Time Surveillance Cameras and Videos | cs.CV | Security concerns has been kept on increasing, so it is important for
everyone to keep their property safe from thefts and destruction. So the need
for surveillance techniques are also increasing. The system has been developed
to detect the motion in a video. A system has been developed for real time
applications by us... | computer science |
25,226 | Adaptive Digital Scan Variable Pixels | cs.CV | The square and rectangular shape of the pixels in the digital images for
sensing and display purposes introduces several inaccuracies in the
representation of digital images. The major disadvantage of square pixel shapes
is the inability to accurately capture and display the details in the objects
having variable orien... | computer science |
25,227 | DeepStereo: Learning to Predict New Views from the World's Imagery | cs.CV | Deep networks have recently enjoyed enormous success when applied to
recognition and classification problems in computer vision, but their use in
graphics problems has been limited. In this work, we present a novel deep
architecture that performs new view synthesis directly from pixels, trained
from a large number of p... | computer science |
25,228 | Autonomous 3D Reconstruction Using a MAV | cs.CV | An approach is proposed for high resolution 3D reconstruction of an object
using a Micro Air Vehicle (MAV). A system is described which autonomously
captures images and performs a dense 3D reconstruction via structure from
motion with no prior knowledge of the environment. Only the MAVs own sensors,
the front facing ca... | computer science |
25,229 | Automatic vehicle tracking and recognition from aerial image sequences | cs.CV | This paper addresses the problem of automated vehicle tracking and
recognition from aerial image sequences. Motivated by its successes in the
existing literature focus on the use of linear appearance subspaces to describe
multi-view object appearance and highlight the challenges involved in their
application as a part ... | computer science |
25,230 | SALSA: A Novel Dataset for Multimodal Group Behavior Analysis | cs.CV | Studying free-standing conversational groups (FCGs) in unstructured social
settings (e.g., cocktail party ) is gratifying due to the wealth of information
available at the group (mining social networks) and individual (recognizing
native behavioral and personality traits) levels. However, analyzing social
scenes involv... | computer science |
25,231 | Person re-identification via efficient inference in fully connected CRF | cs.CV | In this paper, we address the problem of person re-identification problem,
i.e., retrieving instances from gallery which are generated by the same person
as the given probe image. This is very challenging because the person's
appearance usually undergoes significant variations due to changes in
illumination, camera ang... | computer science |
25,232 | R-CNN minus R | cs.CV | Deep convolutional neural networks (CNNs) have had a major impact in most
areas of image understanding, including object category detection. In object
detection, methods such as R-CNN have obtained excellent results by integrating
CNNs with region proposal generation algorithms such as selective search. In
this paper, ... | computer science |
25,233 | Improving Fiber Alignment in HARDI by Combining Contextual PDE Flow with
Constrained Spherical Deconvolution | cs.CV | We propose two strategies to improve the quality of tractography results
computed from diffusion weighted magnetic resonance imaging (DW-MRI) data. Both
methods are based on the same PDE framework, defined in the coupled space of
positions and orientations, associated with a stochastic process describing the
enhancemen... | computer science |
25,234 | Segmentation of Three-dimensional Images with Parametric Active Surfaces
and Topology Changes | cs.CV | In this paper, we introduce a novel parametric method for segmentation of
three-dimensional images. We consider a piecewise constant version of the
Mumford-Shah and the Chan-Vese functionals and perform a region-based
segmentation of 3D image data. An evolution law is derived from energy
minimization problems which pus... | computer science |
25,235 | Deep CNN Ensemble with Data Augmentation for Object Detection | cs.CV | We report on the methods used in our recent DeepEnsembleCoco submission to
the PASCAL VOC 2012 challenge, which achieves state-of-the-art performance on
the object detection task. Our method is a variant of the R-CNN model proposed
Girshick:CVPR14 with two key improvements to training and evaluation. First,
our method ... | computer science |
25,236 | A Novel Feature Extraction Method for Scene Recognition Based on
Centered Convolutional Restricted Boltzmann Machines | cs.CV | Scene recognition is an important research topic in computer vision, while
feature extraction is a key step of object recognition. Although classical
Restricted Boltzmann machines (RBM) can efficiently represent complicated data,
it is hard to handle large images due to its complexity in computation. In this
paper, a n... | computer science |
25,237 | Natural Scene Recognition Based on Superpixels and Deep Boltzmann
Machines | cs.CV | The Deep Boltzmann Machines (DBM) is a state-of-the-art unsupervised learning
model, which has been successfully applied to handwritten digit recognition
and, as well as object recognition. However, the DBM is limited in scene
recognition due to the fact that natural scene images are usually very large.
In this paper, ... | computer science |
25,238 | Targeting Ultimate Accuracy: Face Recognition via Deep Embedding | cs.CV | Face Recognition has been studied for many decades. As opposed to traditional
hand-crafted features such as LBP and HOG, much more sophisticated features can
be learned automatically by deep learning methods in a data-driven way. In this
paper, we propose a two-stage approach that combines a multi-patch deep CNN and
de... | computer science |
25,239 | Salient Object Detection via Objectness Measure | cs.CV | Salient object detection has become an important task in many image
processing applications. The existing approaches exploit background prior and
contrast prior to attain state of the art results. In this paper, instead of
using background cues, we estimate the foreground regions in an image using
objectness proposals ... | computer science |
25,240 | Kernel Cuts: MRF meets Kernel & Spectral Clustering | cs.CV | We propose a new segmentation model combining common regularization energies,
e.g. Markov Random Field (MRF) potentials, and standard pairwise clustering
criteria like Normalized Cut (NC), average association (AA), etc. These
clustering and regularization models are widely used in machine learning and
computer vision, ... | computer science |
25,241 | Unshredding of Shredded Documents: Computational Framework and
Implementation | cs.CV | A shredded document $D$ is a document whose pages have been cut into strips
for the purpose of destroying private, confidential, or sensitive information
$I$ contained in $D$. Shredding has become a standard means of government
organizations, businesses, and private individuals to destroy archival records
that have bee... | computer science |
25,242 | DeepMatching: Hierarchical Deformable Dense Matching | cs.CV | We introduce a novel matching algorithm, called DeepMatching, to compute
dense correspondences between images. DeepMatching relies on a hierarchical,
multi-layer, correlational architecture designed for matching images and was
inspired by deep convolutional approaches. The proposed matching algorithm can
handle non-rig... | computer science |
25,243 | Camera Calibration from Dynamic Silhouettes Using Motion Barcodes | cs.CV | Computing the epipolar geometry between cameras with very different
viewpoints is often problematic as matching points are hard to find. In these
cases, it has been proposed to use information from dynamic objects in the
scene for suggesting point and line correspondences.
We propose a speed up of about two orders of... | computer science |
25,244 | Spectral Collaborative Representation based Classification for Hand
Gestures recognition on Electromyography Signals | cs.CV | In this study, we introduce a novel variant and application of the
Collaborative Representation based Classification in spectral domain for
recognition of the hand gestures using the raw surface Electromyography
signals. The intuitive use of spectral features are explained via circulant
matrices. The proposed Spectral ... | computer science |
25,245 | Occlusion Coherence: Detecting and Localizing Occluded Faces | cs.CV | The presence of occluders significantly impacts object recognition accuracy.
However, occlusion is typically treated as an unstructured source of noise and
explicit models for occluders have lagged behind those for object appearance
and shape. In this paper we describe a hierarchical deformable part model for
face dete... | computer science |
25,246 | A note on patch-based low-rank minimization for fast image denoising | cs.CV | Patch-based low-rank minimization for image processing attracts much
attention in recent years. The minimization of the matrix rank coupled with the
Frobenius norm data fidelity can be solved by the hard thresholding filter with
principle component analysis (PCA) or singular value decomposition (SVD). Based
on this ide... | computer science |
25,247 | Unsupervised Semantic Parsing of Video Collections | cs.CV | Human communication typically has an underlying structure. This is reflected
in the fact that in many user generated videos, a starting point, ending, and
certain objective steps between these two can be identified. In this paper, we
propose a method for parsing a video into such semantic steps in an
unsupervised way. ... | computer science |
25,248 | The Multi-Strand Graph for a PTZ Tracker | cs.CV | High-resolution images can be used to resolve matching ambiguities between
trajectory fragments (tracklets), which is one of the main challenges in
multiple target tracking. A PTZ camera, which can pan, tilt and zoom, is a
powerful and efficient tool that offers both close-up views and wide area
coverage on demand. The... | computer science |
25,249 | Tell and Predict: Kernel Classifier Prediction for Unseen Visual Classes
from Unstructured Text Descriptions | cs.CV | In this paper we propose a framework for predicting kernelized classifiers in
the visual domain for categories with no training images where the knowledge
comes from textual description about these categories. Through our optimization
framework, the proposed approach is capable of embedding the class-level
knowledge fr... | computer science |
25,250 | Automatic Channel Network Extraction from Remotely Sensed Images by
Singularity Analysis | cs.CV | Quantitative analysis of channel networks plays an important role in river
studies. To provide a quantitative representation of channel networks, we
propose a new method that extracts channels from remotely sensed images and
estimates their widths. Our fully automated method is based on a recently
proposed Multiscale S... | computer science |
25,251 | Human Shape Variation - An Efficient Implementation using Skeleton | cs.CV | It is at times important to detect human presence automatically in secure
environments. This needs a shape recognition algorithm that is robust, fast and
has low error rates. The algorithm needs to process camera images quickly to
detect any human in the range of vision, and generate alerts, especially if the
object un... | computer science |
25,252 | An automatic and efficient foreground object extraction scheme | cs.CV | This paper presents a method to differentiate the foreground objects from the
background of a color image. Firstly a color image of any size is input for
processing. The algorithm converts it to a grayscale image. Next we apply canny
edge detector to find the boundary of the foreground object. We concentrate to
find th... | computer science |
25,253 | Spectral Motion Synchronization in SE(3) | cs.CV | This paper addresses the problem of motion synchronization (or averaging) and
describes a simple, closed-form solution based on a spectral decomposition,
which does not consider rotation and translation separately but works straight
in SE(3), the manifold of rigid motions. Besides its theoretical interest,
being the fi... | computer science |
25,254 | Tracking Direction of Human Movement - An Efficient Implementation using
Skeleton | cs.CV | Sometimes a simple and fast algorithm is required to detect human presence
and movement with a low error rate in a controlled environment for security
purposes. Here a light weight algorithm has been presented that generates alert
on detection of human presence and its movement towards a certain direction.
The algorith... | computer science |
25,255 | Long-Range Motion Trajectories Extraction of Articulated Human Using
Mesh Evolution | cs.CV | This letter presents a novel approach to extract reliable dense and
long-range motion trajectories of articulated human in a video sequence.
Compared with existing approaches that emphasize temporal consistency of each
tracked point, we also consider the spatial structure of tracked points on the
articulated human. We ... | computer science |
25,256 | Forming A Random Field via Stochastic Cliques: From Random Graphs to
Fully Connected Random Fields | cs.CV | Random fields have remained a topic of great interest over past decades for
the purpose of structured inference, especially for problems such as image
segmentation. The local nodal interactions commonly used in such models often
suffer the short-boundary bias problem, which are tackled primarily through the
incorporati... | computer science |
25,257 | Multi-Cue Structure Preserving MRF for Unconstrained Video Segmentation | cs.CV | Video segmentation is a stepping stone to understanding video context. Video
segmentation enables one to represent a video by decomposing it into coherent
regions which comprise whole or parts of objects. However, the challenge
originates from the fact that most of the video segmentation algorithms are
based on unsuper... | computer science |
25,258 | Discovering Characteristic Landmarks on Ancient Coins using
Convolutional Networks | cs.CV | In this paper, we propose a novel method to find characteristic landmarks on
ancient Roman imperial coins using deep convolutional neural network models
(CNNs). We formulate an optimization problem to discover class-specific regions
while guaranteeing specific controlled loss of accuracy. Analysis on
visualization of t... | computer science |
25,259 | Learning to Detect Blue-white Structures in Dermoscopy Images with Weak
Supervision | cs.CV | We propose a novel approach to identify one of the most significant
dermoscopic criteria in the diagnosis of Cutaneous Melanoma: the Blue-whitish
structure. In this paper, we achieve this goal in a Multiple Instance Learning
framework using only image-level labels of whether the feature is present or
not. As the output... | computer science |
25,260 | Representing data by sparse combination of contextual data points for
classification | cs.CV | In this paper, we study the problem of using contextual da- ta points of a
data point for its classification problem. We propose to represent a data point
as the sparse linear reconstruction of its context, and learn the sparse
context to gather with a linear classifier in a su- pervised way to increase
its discriminat... | computer science |
25,261 | Supervised Learning of Semantics-Preserving Hash via Deep Convolutional
Neural Networks | cs.CV | This paper presents a simple yet effective supervised deep hash approach that
constructs binary hash codes from labeled data for large-scale image search. We
assume that the semantic labels are governed by several latent attributes with
each attribute on or off, and classification relies on these attributes. Based
on t... | computer science |
25,262 | Polarimetric Hierarchical Semantic Model and Scattering Mechanism Based
PolSAR Image Classification | cs.CV | For polarimetric SAR (PolSAR) image classification, it is a challenge to
classify the aggregated terrain types, such as the urban area, into semantic
homogenous regions due to sharp bright-dark variations in intensity. The
aggregated terrain type is formulated by the similar ground objects aggregated
together. In this ... | computer science |
25,263 | Compressive Deconvolution in Medical Ultrasound Imaging | cs.CV | The interest of compressive sampling in ultrasound imaging has been recently
extensively evaluated by several research teams. Following the different
application setups, it has been shown that the RF data may be reconstructed
from a small number of measurements and/or using a reduced number of ultrasound
pulse emission... | computer science |
25,264 | Pose Embeddings: A Deep Architecture for Learning to Match Human Poses | cs.CV | We present a method for learning an embedding that places images of humans in
similar poses nearby. This embedding can be used as a direct method of
comparing images based on human pose, avoiding potential challenges of
estimating body joint positions. Pose embedding learning is formulated under a
triplet-based distanc... | computer science |
25,265 | Convolutional Color Constancy | cs.CV | Color constancy is the problem of inferring the color of the light that
illuminated a scene, usually so that the illumination color can be removed.
Because this problem is underconstrained, it is often solved by modeling the
statistical regularities of the colors of natural objects and illumination. In
contrast, in thi... | computer science |
25,266 | Cross Modal Distillation for Supervision Transfer | cs.CV | In this work we propose a technique that transfers supervision between images
from different modalities. We use learned representations from a large labeled
modality as a supervisory signal for training representations for a new
unlabeled paired modality. Our method enables learning of rich representations
for unlabele... | computer science |
25,267 | Fine-grained Recognition Datasets for Biodiversity Analysis | cs.CV | In the following paper, we present and discuss challenging applications for
fine-grained visual classification (FGVC): biodiversity and species analysis.
We not only give details about two challenging new datasets suitable for
computer vision research with up to 675 highly similar classes, but also
present first result... | computer science |
25,268 | Parsimonious Labeling | cs.CV | We propose a new family of discrete energy minimization problems, which we
call parsimonious labeling. Specifically, our energy functional consists of
unary potentials and high-order clique potentials. While the unary potentials
are arbitrary, the clique potentials are proportional to the {\em diversity} of
set of the ... | computer science |
25,269 | Autoencoding the Retrieval Relevance of Medical Images | cs.CV | Content-based image retrieval (CBIR) of medical images is a crucial task that
can contribute to a more reliable diagnosis if applied to big data. Recent
advances in feature extraction and classification have enormously improved CBIR
results for digital images. However, considering the increasing accessibility
of big da... | computer science |
25,270 | Visual Data Deblocking using Structural Layer Priors | cs.CV | The blocking artifact frequently appears in compressed real-world images or
video sequences, especially coded at low bit rates, which is visually annoying
and likely hurts the performance of many computer vision algorithms. A
compressed frame can be viewed as the superimposition of an intrinsic layer and
an artifact on... | computer science |
25,271 | Learning Better Encoding for Approximate Nearest Neighbor Search with
Dictionary Annealing | cs.CV | We introduce a novel dictionary optimization method for high-dimensional
vector quantization employed in approximate nearest neighbor (ANN) search.
Vector quantization methods first seek a series of dictionaries, then
approximate each vector by a sum of elements selected from these dictionaries.
An optimal series of di... | computer science |
25,272 | Beyond Semantic Image Segmentation : Exploring Efficient Inference in
Video | cs.CV | We explore the efficiency of the CRF inference module beyond image level
semantic segmentation. The key idea is to combine the best of two worlds of
semantic co-labeling and exploiting more expressive models. Similar to
[Alvarez14] our formulation enables us perform inference over ten thousand
images within seconds. On... | computer science |
25,273 | Joint Calibration for Semantic Segmentation | cs.CV | Semantic segmentation is the task of assigning a class-label to each pixel in
an image. We propose a region-based semantic segmentation framework which
handles both full and weak supervision, and addresses three common problems:
(1) Objects occur at multiple scales and therefore we should use regions at
multiple scales... | computer science |
25,274 | DCTNet : A Simple Learning-free Approach for Face Recognition | cs.CV | PCANet was proposed as a lightweight deep learning network that mainly
leverages Principal Component Analysis (PCA) to learn multistage filter banks
followed by binarization and block-wise histograming. PCANet was shown worked
surprisingly well in various image classification tasks. However, PCANet is
data-dependence h... | computer science |
25,275 | Spotlight the Negatives: A Generalized Discriminative Latent Model | cs.CV | Discriminative latent variable models (LVM) are frequently applied to various
visual recognition tasks. In these systems the latent (hidden) variables
provide a formalism for modeling structured variation of visual features.
Conventionally, latent variables are de- fined on the variation of the
foreground (positive) cl... | computer science |
25,276 | Towards Good Practices for Very Deep Two-Stream ConvNets | cs.CV | Deep convolutional networks have achieved great success for object
recognition in still images. However, for action recognition in videos, the
improvement of deep convolutional networks is not so evident. We argue that
there are two reasons that could probably explain this result. First the
current network architecture... | computer science |
25,277 | Iris Recognition Using Scattering Transform and Textural Features | cs.CV | Iris recognition has drawn a lot of attention since the mid-twentieth
century. Among all biometric features, iris is known to possess a rich set of
features. Different features have been used to perform iris recognition in the
past. In this paper, two powerful sets of features are introduced to be used
for iris recogni... | computer science |
25,278 | Feature Representation in Convolutional Neural Networks | cs.CV | Convolutional Neural Networks (CNNs) are powerful models that achieve
impressive results for image classification. In addition, pre-trained CNNs are
also useful for other computer vision tasks as generic feature extractors. This
paper aims to gain insight into the feature aspect of CNN and demonstrate other
uses of CNN... | computer science |
25,279 | Neural Network Classifiers for Natural Food Products | cs.CV | Two cheap, off-the-shelf machine vision systems (MVS), each using an
artificial neural network (ANN) as classifier, were developed, improved and
evaluated to automate the classification of tomato ripeness and acceptability
of eggs, respectively. Six thousand color images of human-graded tomatoes and
750 images of human... | computer science |
25,280 | Understanding Intra-Class Knowledge Inside CNN | cs.CV | Convolutional Neural Network (CNN) has been successful in image recognition
tasks, and recent works shed lights on how CNN separates different classes with
the learned inter-class knowledge through visualization. In this work, we
instead visualize the intra-class knowledge inside CNN to better understand how
an object ... | computer science |
25,281 | Learning Structured Ordinal Measures for Video based Face Recognition | cs.CV | This paper presents a structured ordinal measure method for video-based face
recognition that simultaneously learns ordinal filters and structured ordinal
features. The problem is posed as a non-convex integer program problem that
includes two parts. The first part learns stable ordinal filters to project
video data in... | computer science |
25,282 | Towards Effective Codebookless Model for Image Classification | cs.CV | The bag-of-features (BoF) model for image classification has been thoroughly
studied over the last decade. Different from the widely used BoF methods which
modeled images with a pre-trained codebook, the alternative codebook free image
modeling method, which we call Codebookless Model (CLM), attracted little
attention.... | computer science |
25,283 | Generalized Video Deblurring for Dynamic Scenes | cs.CV | Several state-of-the-art video deblurring methods are based on a strong
assumption that the captured scenes are static. These methods fail to deblur
blurry videos in dynamic scenes. We propose a video deblurring method to deal
with general blurs inherent in dynamic scenes, contrary to other methods. To
handle locally v... | computer science |
25,284 | Multi-Type Activity Recognition in Robot-Centric Scenarios | cs.CV | Activity recognition is very useful in scenarios where robots interact with,
monitor or assist humans. In the past years many types of activities -- single
actions, two persons interactions or ego-centric activities, to name a few --
have been analyzed. Whereas traditional methods treat such types of activities
separat... | computer science |
25,285 | Deep filter banks for texture recognition, description, and segmentation | cs.CV | Visual textures have played a key role in image understanding because they
convey important semantics of images, and because texture representations that
pool local image descriptors in an orderless manner have had a tremendous
impact in diverse applications. In this paper we make several contributions to
texture under... | computer science |
25,286 | Robot In a Room: Toward Perfect Object Recognition in Closed
Environments | cs.CV | While general object recognition is still far from being solved, this paper
proposes a way for a robot to recognize every object at an almost human-level
accuracy. Our key observation is that many robots will stay in a relatively
closed environment (e.g. a house or an office). By constraining a robot to stay
in a limit... | computer science |
25,287 | Riemannian Dictionary Learning and Sparse Coding for Positive Definite
Matrices | cs.CV | Data encoded as symmetric positive definite (SPD) matrices frequently arise
in many areas of computer vision and machine learning. While these matrices
form an open subset of the Euclidean space of symmetric matrices, viewing them
through the lens of non-Euclidean Riemannian geometry often turns out to be
better suited... | computer science |
25,288 | Robust Performance-driven 3D Face Tracking in Long Range Depth Scenes | cs.CV | We introduce a novel robust hybrid 3D face tracking framework from RGBD video
streams, which is capable of tracking head pose and facial actions without
pre-calibration or intervention from a user. In particular, we emphasize on
improving the tracking performance in instances where the tracked subject is at
a large dis... | computer science |
25,289 | Deep Perceptual Mapping for Thermal to Visible Face Recognition | cs.CV | Cross modal face matching between the thermal and visible spectrum is a much
de- sired capability for night-time surveillance and security applications. Due
to a very large modality gap, thermal-to-visible face recognition is one of the
most challenging face matching problem. In this paper, we present an approach
to br... | computer science |
25,290 | LooseCut: Interactive Image Segmentation with Loosely Bounded Boxes | cs.CV | One popular approach to interactively segment the foreground object of
interest from an image is to annotate a bounding box that covers the foreground
object. Then, a binary labeling is performed to achieve a refined segmentation.
One major issue of the existing algorithms for such interactive image
segmentation is the... | computer science |
25,291 | Face Alignment Assisted by Head Pose Estimation | cs.CV | In this paper we propose a supervised initialization scheme for cascaded face
alignment based on explicit head pose estimation. We first investigate the
failure cases of most state of the art face alignment approaches and observe
that these failures often share one common global property, i.e. the head pose
variation i... | computer science |
25,292 | DeepFont: Identify Your Font from An Image | cs.CV | As font is one of the core design concepts, automatic font identification and
similar font suggestion from an image or photo has been on the wish list of
many designers. We study the Visual Font Recognition (VFR) problem, and advance
the state-of-the-art remarkably by developing the DeepFont system. First of
all, we bu... | computer science |
25,293 | Unconstrained Facial Landmark Localization with Backbone-Branches
Fully-Convolutional Networks | cs.CV | This paper investigates how to rapidly and accurately localize facial
landmarks in unconstrained, cluttered environments rather than in the well
segmented face images. We present a novel Backbone-Branches Fully-Convolutional
Neural Network (BB-FCN), which produces facial landmark response maps directly
from raw images ... | computer science |
25,294 | Lifting GIS Maps into Strong Geometric Context for Scene Understanding | cs.CV | Contextual information can have a substantial impact on the performance of
visual tasks such as semantic segmentation, object detection, and geometric
estimation. Data stored in Geographic Information Systems (GIS) offers a rich
source of contextual information that has been largely untapped by computer
vision. We prop... | computer science |
25,295 | Unsupervised Decision Forest for Data Clustering and Density Estimation | cs.CV | An algorithm to improve performance parameter for unsupervised decision
forest clustering and density estimation is presented. Specifically, a dual
assignment parameter is introduced as a density estimator by combining Random
Forest and Gaussian Mixture Model. The Random Forest method has been
specifically applied to c... | computer science |
25,296 | A Deep Hashing Learning Network | cs.CV | Hashing-based methods seek compact and efficient binary codes that preserve
the neighborhood structure in the original data space. For most existing
hashing methods, an image is first encoded as a vector of hand-crafted visual
feature, followed by a hash projection and quantization step to get the compact
binary vector... | computer science |
25,297 | Diagnosing State-Of-The-Art Object Proposal Methods | cs.CV | Object proposal has become a popular paradigm to replace exhaustive sliding
window search in current top-performing methods in PASCAL VOC and ImageNet.
Recently, Hosang et al. conduct the first unified study of existing methods' in
terms of various image-level degradations. On the other hand, the vital
question "what o... | computer science |
25,298 | Multi-Face Tracking by Extended Bag-of-Tracklets in Egocentric Videos | cs.CV | Wearable cameras offer a hands-free way to record egocentric images of daily
experiences, where social events are of special interest. The first step
towards detection of social events is to track the appearance of multiple
persons involved in it. In this paper, we propose a novel method to find
correspondences of mult... | computer science |
25,299 | Driver Gaze Region Estimation Without Using Eye Movement | cs.CV | Automated estimation of the allocation of a driver's visual attention may be
a critical component of future Advanced Driver Assistance Systems. In theory,
vision-based tracking of the eye can provide a good estimate of gaze location.
In practice, eye tracking from video is challenging because of sunglasses,
eyeglass re... | computer science |
25,300 | RBIR Based on Signature Graph | cs.CV | This paper approaches the image retrieval system on the base of visual
features local region RBIR (region-based image retrieval). First of all, the
paper presents a method for extracting the interest points based on
Harris-Laplace to create the feature region of the image. Next, in order to
reduce the storage space and... | computer science |
25,301 | Multiscale Adaptive Representation of Signals: I. The Basic Framework | cs.CV | We introduce a framework for designing multi-scale, adaptive, shift-invariant
frames and bi-frames for representing signals. The new framework, called
AdaFrame, improves over dictionary learning-based techniques in terms of
computational efficiency at inference time. It improves classical multi-scale
basis such as wave... | computer science |
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