NDLI: Online motion classification using support vector machines

Content Provider	IEEE Xplore Digital Library
Author	Dongwei Cao Masoud, O.T. Boley, D. Papanikolopoulos, N.
Copyright Year	2004
Description	Author affiliation: Dept. of Comput. Sci. & Eng., Minnesota Univ., Minneapolis, MN, USA (Dongwei Cao; Masoud, O.T.; Boley, D.; Papanikolopoulos, N.)
Abstract	We propose a motion recognition strategy that represents a videoclip as a set of filtered images, each of which encodes a short period of motion history. Given a set of videoclips whose motion types are known, a filtered image classifier is built using support vector machines. In offline classification, the label of a test videoclip is obtained by applying majority voting over its filtered images. In online classification, the most probable type of action at an instance is determined by applying the majority voting over the most recent filtered images, which are within a sliding window. The effectiveness of this strategy was demonstrated on real datasets where the videoclips were recorded using a fixed camera whose optical axis is perpendicular to the person's trajectory. In offline recognition, the proposed strategy outperforms a principal component analysis based recognition algorithm. In online recognition, the proposed strategy cannot only classify motions correctly and identify the transition between different types of motions, but also identify the existence of an unknown motion type. This latter capability and the efficiency of the proposed strategy make it possible to create a real-time motion recognition system that can not only make classifications in real-time, but also learn new types of actions and recognize them in the future.
Sponsorship	IEEE Robotics and Automation Soc
Starting Page	2291
Ending Page	2296
File Size	431789
Page Count	6
File Format	PDF
ISBN	0780382323
ISSN	10504729
DOI	10.1109/ROBOT.2004.1307403
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-04-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Support vector machine classification Voting Optical filters Real time systems Image recognition History Testing Cameras Optical recording
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software

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

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