NDLI: A fuzzy logic-based system for the automation of human behavior recognition using machine vision in intelligent environments

Content Provider	Springer Nature Link
Author	Yao, Bo Hagras, Hani Alhaddad, Mohammed J. Alghazzawi, Daniyal
Copyright Year	2014
Abstract	The recent years have witnessed significant progress in the automation of human behavior recognition using machine vision in order to realize intelligent environments which are capable of detecting users’ actions and gestures so that the needed services can be provided automatically and instantly for maximizing the user comfort and safety as well as minimizing energy. However, the majority of traditional human behavior machine vision-based recognition approaches rely on assumptions (such as known spatial locations and temporal segmentations) or computationally expensive approaches (such as sliding window search through a spatio-temporal volume). Hence, it is difficult for such methods to scale up and handle the high uncertainty levels and complexities available in real-world applications. This paper proposes a novel fuzzy machine vision-based framework for efficient humans’ behavior recognition. A model-based feature set is utilized to extract visual feature cues including silhouette slices and movement speed from the human silhouette in video sequences which are analyzed as inputs by the proposed fuzzy system. We have employed fuzzy c-means clustering to learn the membership functions of the proposed fuzzy system. The behavior recognition was implemented via selecting the best candidate’s behavior category with the highest output degree as the recognized behavior. We have successfully tested our system on the publicly available Weizmann human action dataset where our fuzzy-based system produced an average recognition accuracy of 94.03 %, which outperformed the traditional non-fuzzy systems based on hidden Markov models and other state-of-the-art approaches which were applied on the Weizmann dataset.
Starting Page	499
Ending Page	506
Page Count	8
File Format	PDF
ISSN	14327643
Journal	Soft Computing
Volume Number	19
Issue Number	2
e-ISSN	14337479
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2014-04-30
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Fuzzy logic system Human behavior recognition Action classification Computational Intelligence Artificial Intelligence (incl. Robotics) Mathematical Logic and Foundations Control, Robotics, Mechatronics
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Software Geometry and Topology

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

Fuzzy classification in dynamic environments

Fuzzy region assignment for visual tracking

Assessment of learning in environments interactive through fuzzy cognitive maps

MSAFIS: an evolving fuzzy inference system

Efficient pattern classification model with neuro-fuzzy networks

Solving fuzzy linear systems

Patent value analysis using support vector machines

Human face recognition using fuzzy multilayer perceptron

Recent advances in machine intelligence

A fuzzy logic-based system for the automation of human behavior recognition using machine vision in intelligent environments

Similar Documents

Fuzzy classification in dynamic environments

Fuzzy region assignment for visual tracking

Assessment of learning in environments interactive through fuzzy cognitive maps

MSAFIS: an evolving fuzzy inference system

Efficient pattern classification model with neuro-fuzzy networks

Solving fuzzy linear systems

Patent value analysis using support vector machines

Human face recognition using fuzzy multilayer perceptron

Recent advances in machine intelligence

A fuzzy logic-based system for the automation of human behavior recognition using machine vision in intelligent environments