Discovering unusual behavior patterns from motion data

Kai Lin Pang, Guan Hong Chen, Wei-Guang Teng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

As there are more and more surveillance cameras installed in public places, a challenging problem is to discover unusual behavior patterns from a huge amount of video data. However, this task is currently only feasible for human beings because both object recognition and intention detection are still difficult for computer vision. Recently, the development of low-cost depth cameras significantly improves the efficiency and effectiveness of capturing motion data. We thus propose in this work an algorithmic scheme that extracts unusual behavior patterns from motion capture data. Specifically, feature extraction and data clustering techniques are applied in our scheme so as to detect such outlier patterns. Example applications of our scheme include public area surveillance and home healthcare.

Original languageEnglish
Title of host publication2013 IEEE International Conference on Consumer Electronics, ICCE 2013
Pages242-243
Number of pages2
DOIs
Publication statusPublished - 2013 Apr 24
Event2013 IEEE International Conference on Consumer Electronics, ICCE 2013 - Las Vegas, NV, United States
Duration: 2013 Jan 112013 Jan 14

Publication series

NameDigest of Technical Papers - IEEE International Conference on Consumer Electronics
ISSN (Print)0747-668X

Other

Other2013 IEEE International Conference on Consumer Electronics, ICCE 2013
CountryUnited States
CityLas Vegas, NV
Period13-01-1113-01-14

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

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