Activity awareness: From predefined events to new pattern discovery

Yunqian Ma, Ben Miller, Pradeep Buddharaju, Mike Bazakos

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

9 Scopus citations

Abstract

Applying advanced video technology to understand (human) activity and intent, including the interaction of multiple people and objects, is becoming increasingly important, especially for intelligent video surveillance. Recently, technical interest in video surveillance has moved from low-level processing modules, such as motion detection and motion tracking, to activity awareness and more complex scene understanding. This paper presents an integrated video surveillance system at Honeywell labs, which detects predefined activities with improved robustness. Also, we present the 'new activity' detection (pattern discovery), which can automatically capture new activities, and present the newly detected activities to the operator who checks for their validity and adds them into the activity models. Moreover, we present a torso angle feature, which represents people posture, to detect activities, such as people falling. We used real world data sets to show the effectiveness of our proposed method.

Original languageEnglish (US)
Title of host publicationProceedings of the Fourth IEEE International Conference on Computer Vision Systems, ICVS'06
Number of pages1
DOIs
StatePublished - Oct 10 2006
EventFourth IEEE International Conference on Computer Vision Systems, ICVS'06 - New York, NY, United States
Duration: Jan 4 2006Jan 7 2006

Publication series

NameProceedings of the Fourth IEEE International Conference on Computer Vision Systems, ICVS'06
Volume2006

Other

OtherFourth IEEE International Conference on Computer Vision Systems, ICVS'06
CountryUnited States
CityNew York, NY
Period1/4/061/7/06

Cite this