NDLI: Object detection and classification in surveillance system

Content Provider	IEEE Xplore Digital Library
Author	Varma, S. Sreeraj, M.
Copyright Year	2013
Description	Author affiliation: Dept. of Comput. Sci. & Eng., Fed. Inst. of Sci. & Technol. (FISAT), Ernakulam, India (Varma, S.; Sreeraj, M.)
Abstract	Object Detection and Tracking in Surveillance System is inevitable in the present scenario, as it is not possible for a person to continuously monitor the video clips in real time. We propose an efficient and novel system for detecting moving objects in a surveillance video and predict whether it is a human or not. In order to account for faster object detection, we use an established Background Subtraction Algorithm known as Mixture of Gaussians. A set of simple and efficient features are extracted and provided to Support Vector Machine. The performance of the system is evaluated with different kernels of SVM and also for K Nearest Neighbor Classifier with its various distance metrics. The system is evaluated using statistical measurements, and the experiments resulted in average F measure of 86.925% and thus prove the efficiency of the novel system.
Sponsorship	IEEE Kerala Sect.
Starting Page	299
Ending Page	303
File Size	1181727
Page Count	5
File Format	PDF
e-ISBN	9781479921782
DOI	10.1109/RAICS.2013.6745491
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-19
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Computer vision Object Detection Background Subtraction Surveillance SVM Classification Object detection Streaming media Feature extraction Kernel Surveillance System
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Pedestrian detection using background subtraction assisted Support Vector Machine

A novel SVM video object extraction technology

Object Detection by Spatial Salience Region Features

Contextualizing object detection and classification

Moving vehicle classification

Home environment fall detection system based on a cascaded multi-SVM classifier

Three viewpoints toward exemplar SVM

Learning equivariant structured output SVM regressors

SVM Based System for classification of Microcalcifications in Digital Mammograms

Object detection and classification in surveillance system

Similar Documents

Pedestrian detection using background subtraction assisted Support Vector Machine

A novel SVM video object extraction technology

Object Detection by Spatial Salience Region Features

Contextualizing object detection and classification

Moving vehicle classification

Home environment fall detection system based on a cascaded multi-SVM classifier

Three viewpoints toward exemplar SVM

Learning equivariant structured output SVM regressors

SVM Based System for classification of Microcalcifications in Digital Mammograms

Object detection and classification in surveillance system