An efficient method of human behavior recognition in smart environments

Author

Hu, Chun-Hua ; Wo, Song-Lin

Author_Institution

Sch. of Electr. & Inf. Eng., Jiangsu Teacher Univ. of Technol., Changzhou, China

Volume

12

fYear

2010

fDate

22-24 Oct. 2010

Abstract

The task of reliably detecting and recognizing the action of a specific person for smart space is challenging. In this paper, an efficient vision-based method of human behavior recognition in smart environments is proposed, which utilizes the template match method by edge gradient orientation method for extracting the critical points of human and using the Hidden Markov Model (HMM) to construct the behavior recognition classifier. Various experiments are carried out and the results demonstrate the robustness and reliability in human behavior recognition.

Keywords

behavioural sciences computing; computer vision; edge detection; feature extraction; gradient methods; hidden Markov models; intelligent robots; Hidden Markov Model; action detection reliability; action recognition reliability; critical points extraction; edge gradient orientation method; human behavior recognition; smart space; template match method; vision-based method; behavior recognition; gradient orientation; vision-based;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Application and System Modeling (ICCASM), 2010 International Conference on

Conference_Location

Taiyuan

Print_ISBN

978-1-4244-7235-2

Electronic_ISBN

978-1-4244-7237-6

Type

conf

DOI

10.1109/ICCASM.2010.5622464

Filename

5622464