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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  
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

Simone Chiappino, Lucio Marcenaro, Carlo S. Regazzoni
2014 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)  
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

Samson Hansen Sackey, Samuel Nartey Kofie, Abdul Karim Armah
2019 Zenodo  
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

Prajakta Sunil Gupta, Gadicha V.B
2017 International Journal of Recent Scientific Research  
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

Concetto Spampinato, Vasileios Mezaris, Benoit Huet, Jacco van Ossenbruggen
2014 Ecological Informatics  
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

Yordanka Karayaneva, Sara Sharifzadeh, Yanguo Jing, Kevin Chetty, Bo Tan
2019 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA)  
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

R. Venkatesh Babu
2013 2013 IEEE International Conference on Image Processing  
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

Fei Yang, Hong Jiang, Zuowei Shen, Wei Deng, Dimitris Metaxas
2013 2013 IEEE International Conference on Image Processing  
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

Muhammad Sajjad, Irfan Mehmood, Sung Baik
2014 Sensors  
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

Eric Jardim, Xiao Bian, Eduardo A. B. da Silva, Sergio L. Netto, Hamid Krim
2015 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)  
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

Mithilesh Kumar JHA, Brejesh Lall, Sumantra Roy
2014 Journal of Pattern Recognition Research  
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

Huamin Ren, Hong Pan, Soren Ingvor Olsen, Morten Borno Jensen, Thomas B. Moeslund
2016 2016 13th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)  
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

Shuang Wang, Lijuan Cui, Dianchao Liu, Robert Huck, Pramode Verma, James J. Sluss, Samuel Cheng
2012 IEEE transactions on intelligent transportation systems (Print)  
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

R. Rajitha Jasmine, Dr. K. K. Thyagharajan
2015 International Journal of Engineering Research and  
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

Qiang Zhu, S. Avidan, Kwang-Ting Cheng
2005 Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1  
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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