A study of human activity sequence segmentation based on gaussian model

Author

Xiong Wei ; Zhang Er-hu

Author_Institution

Dept. of Inf. Sci., Xi´an Univ. of Technol., Xi´an, China

Volume

1

fYear

2011

fDate

15-17 Oct. 2011

Firstpage

390

Lastpage

393

Abstract

Human activity analysis based on video is a hot research topic in the field of computer vision, in which segmentation of human activity sequence is a fundamental question. In this paper, we present a new unsupervised segmentation method for human activity sequence. The main idea of this method is that the most dramatic point, which is regarded as the split point, is detected by gaussian model according to human action´s mutation in the video. Experimental results show the feasibility and effectiveness of the segmentation algorithm in this paper.

Keywords

Gaussian processes; computer vision; image segmentation; image sequences; video signal processing; Gaussian model; computer vision; dramatic point; human action mutation; human activity analysis; human activity sequence segmentation; split poin; unsupervised segmentation; video; Computer vision; Hidden Markov models; Humans; Image segmentation; Motion segmentation; Pattern recognition; Video sequences; gaussian model; human action mutation; segmentation of activity sequence; unsupervised method;

fLanguage

English

Publisher

ieee

Conference_Titel

Image and Signal Processing (CISP), 2011 4th International Congress on

Conference_Location

Shanghai

Print_ISBN

978-1-4244-9304-3

Type

conf

DOI

10.1109/CISP.2011.6099938

Filename

6099938