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Abnormal behavior detection using sparse representations through sequential generalization of K-means
2020
Turkish Journal of Electrical Engineering and Computer Sciences
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This study presents a new high-performance 5 framework for detecting behavioral abnormalities in video streams by utilizing only the patterns for normal behaviors. 6 In this paper, we used a hybrid descriptor ...
(OMP) algorithm was utilized to recover high-dimensional sparse features 11 when referring to a few numbers of noisy linear measurements. ...
Therefore, in this study, a new effective framework to detect abnormalities based on SGK and OMP 9 algorithms has been presented. ...
doi:10.3906/elk-1904-187
fatcat:4awbmnhaungkvhyosfpcianrse
Information Bottleneck-based relevant knowledge representation in large-scale video surveillance systems
2014
2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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In this paper, a novel representation technique for sparse information, based on information theory, is presented. ...
Proposed experiments show how the so called information bottleneck-based SOM selection for knowledge modelling, can be applied to the field of crowd monitoring for people density map estimation and event ...
The proposed framework has been applied to crowd monitoring domain for people density estimation and event recognition on video real sequences extracted from public database PETS [15] . ...
doi:10.1109/icassp.2014.6854426
dblp:conf/icassp/ChiappinoMR14
fatcat:7cez5rpxevbuddpvndjpvlryjq
A Randomized Approach to Sparse Subspace Clustering using Spectral clustering
2019
Zenodo
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A random subspace is expressed into sparse representation called Randomized Sparse Subspace Clustering (RSSC), which is capable of intensifying the precision of the subspace cluster on real-life datasets ...
The steps taken to segment an in-motion object from its training set is a major feature in a lot of computer vision applications ranging from motion segmentation to image recognition. ...
CONCLUSION Conclusively, we have presented a concise approach to subspace clustering based on sparse representation. ...
doi:10.5281/zenodo.3373651
fatcat:u65sq5eu45bhxpn36wz6vb3qye
Enhancement of low quality degraded video using haar wavelet decomposition technique
2017
International Journal of Recent Scientific Research
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Zhong, 2014] proposed method based on a sparse collaborative model that exploits both holistic templates and local representations to account for drastic appearance changes. ...
A new framework for removing impulse noise from images is presented in which the nature of the filtering operation is conditioned on a state variable defined as the output of a classifier that operates ...
doi:10.24327/ijrsr.2017.0803.0084
fatcat:qioyi5tqjveirle2zw2egvmu5e
Editorial — Special issue on multimedia in ecology
2014
Ecological Informatics
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by expert ecologists to proactively provide analytical information on the environment. ...
Sensors are used increasingly in a range of monitoring or exploratory applications, in particular for biological surveys: for instance, the Xeno-canto project 1 has collected thousands of bird sounds over ...
We would like to thank, first, the authors for their contribution to this special issue, then, all the reviewers for the effort and time spent to provide thorough reviews and valuable suggestions on the ...
doi:10.1016/j.ecoinf.2014.03.001
fatcat:zvfaqhm2hrehjci7jsemjgms7u
Sparse Feature Extraction for Activity Detection Using Low-Resolution IR Streams
2019
2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA)
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To prove the availability of the sparse features, we also compare the classification results of the noisy data based sparse features and non-sparse based features respectively. ...
Therefore, our analysis is based on the temporal variation of the pixels in vectorised sequences of several IR frames, which results in a high dimensional feature space and an "n p" problem. ...
based on sparse techniques and their tolerance to noise was found. ...
doi:10.1109/icmla.2019.00296
dblp:conf/icmla/KarayanevaSJCT19
fatcat:mk2uf6rbnffcrgtkxcg5wup3ma
Real-time robust tracking via sparse representation: A mode-seeking approach
2013
2013 IEEE International Conference on Image Processing
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In this paper, we propose a robust realtime tracking as a mode seeking process over likelihood map via sparse representation. ...
We quantify the performance of the proposed tracker on many video sequences with various challenges involving occlusion, illumination change and pose variations. ...
INTRODUCTION Object tracking is one of the critical tasks in computer vision applications such as video surveillance and monitoring. ...
doi:10.1109/icip.2013.6738807
dblp:conf/icip/Babu13
fatcat:okjks5ppibfuhgnu2wuq4nna7e
Adaptive low rank and sparse decomposition of video using compressive sensing
2013
2013 IEEE International Conference on Image Processing
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We develop a new method that performs video reconstruction by low rank and sparse decomposition adaptively. Background subtraction becomes part of the reconstruction. ...
We will present experimental results to demonstrate the advantages of the proposed method. ...
Since videos are known to have a sparse representation in some transform basis (e.g. total variation, wavelet or framelet, etc.), the compressive sensing theory can be applied to compress video at the ...
doi:10.1109/icip.2013.6738210
dblp:conf/icip/YangJSDM13
fatcat:vbovlfglozdbvhkhtpeqfmi2zy
Sparse Representations-Based Super-Resolution of Key-Frames Extracted from Frames-Sequences Generated by a Visual Sensor Network
2014
Sensors
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A novel effective SR scheme is applied at BS to produce a high-resolution (HR) output from the received key-frames. ...
The proposed SR scheme uses optimized orthogonal matching pursuit (OOMP) for sparse-representation recovery in SR. ...
Sparse representations are determined using a hybrid regularization method and then applied to the individual sub-frames to compute the HR version. Zhang et al. ...
doi:10.3390/s140203652
pmid:24566632
pmcid:PMC3958298
fatcat:zou3sq7ksnbmtkue4lsqj6iyqm
On the detection of abandoned objects with a moving camera using robust subspace recovery and sparse representation
2015
2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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We consider the application of sparse-representation and robust-subspace-recovery techniques to detect abandoned objects in a target video acquired with a moving camera. ...
A three-step procedure is then presented adapting a previous low-rank and sparse image representation to the problem at hand. ...
CONCLUSIONS We have presented a new approach for detecting changes in moving camera captured videos sequences by applying sparse representations based on the RoSuRe technique. ...
doi:10.1109/icassp.2015.7178179
dblp:conf/icassp/JardimBSNK15
fatcat:gg7us3vp4fdkrbbgcfjs3quehi
DEMD-Based Image Compression Scheme in a Compressive Sensing Framework
2014
Journal of Pattern Recognition Research
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The efficient representation of the DEMD residue is achieved as a sparse coding solution based on a Discrete Wavelet Transform (DWT)-based sparsification. ...
This paper investigates a new approach for an efficient representation of a class of images from textured videos and different BRDF images of an object, using sparse representation of the Directional Empirical ...
The efficient representation problem of the DEMD residue of the frame, is modeled as a sparse coding solution based on a wavelet-based sparsification, whose solution is computed using convex optimisation ...
doi:10.13176/11.580
fatcat:kbo2opymuzeelkz57s5v4xdcbi
An in-depth study of sparse codes on abnormality detection
2016
2016 13th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)
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Sparse representation has been applied successfully in abnormal event detection, in which the baseline is to learn a dictionary accompanied by sparse codes. ...
We also propose our framework of combining sparse codes with different detection methods. ...
Furthermore, we explore the sparse codes and compare different methods to determine whether a testing code is an anomaly or not. ...
doi:10.1109/avss.2016.7738016
dblp:conf/avss/RenPOJM16
fatcat:raj3mc6iybe27e6xcldgjbtyje
Vehicle Identification Via Sparse Representation
2012
IEEE transactions on intelligent transportation systems (Print)
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In this paper, we propose a system using video cameras to perform vehicle identification. ...
We tackle this problem through reconstructing an input by using multiple linear regression models and compressed sensing, which provide new ways to deal with three crucial issues in vehicle identification ...
Based on the idea of sparse representation for objection classification and identification, we propose a video based vehicle identification framework in this paper. ...
doi:10.1109/tits.2011.2171034
fatcat:oksj3rfxwvh5xduk5dekgk4rva
Study on Recent Approaches for Human Action Recognition in Real Time
2015
International Journal of Engineering Research and
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Even though, traditional methods have achieved greater success on several human actions. But, still it is a challenging problem to recognize human action. ...
The action recognition application includes CCTV, video indexing, patient monitoring systems and HCI systems. ...
sparse coding framework; finally, a linear SVM is applied as the classifier to predict the action class. ...
doi:10.17577/ijertv4is080577
fatcat:hikmv56t6jc5la7ipcny5u4kha
Learning a sparse, corner-based representation for time-varying background modelling
2005
Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1
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Experiments on challenging video clips demonstrate that the proposed method achieves a higher accuracy in detecting the foreground objects than the existing methods. ...
Experiments on challenging video clips demonstrate that the proposed method achieves a higher accuracy in detecting the foreground objects than the existing methods. ...
In this paper, we propose a novel modelling technique, which is based on a sparse feature set of detected corners in each video frame. ...
doi:10.1109/iccv.2005.134
dblp:conf/iccv/ZhuAC05
fatcat:hexsdms7lzcjpl5mijxfixcbau
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