Title
Handheld object detection and its related event analysis using ratio histogram and mixture of HMMs
Abstract
This paper proposes a novel system to analyze human-object interaction events happening between hands and faces in real time. Two challenging problems in this event analysis must be addressed, i.e., there is no prior knowledge (like shape, color, size, and texture) about the handheld objects, and there are large spatial-temporal variations in event representation. For the first challenge, a novel ratio histogram is proposed to find important color bins to locate handheld objects and their trajectories via a code book technique. This scheme is different from other boosted methods which require very time-consuming estimations to search reliable body configurations. For the second challenge, a mixture of HMMs is proposed to describe an event not only from its dynamic context but also its multiplicity context. It can be performed in real time because an exhaustive search process is avoided to find possible interaction pairs between objects and body parts.
Year
DOI
Venue
2014
10.1016/j.jvcir.2014.05.009
Journal of Visual Communication and Image Representation
Keywords
Field
DocType
hmms,ratio histogram,event multiplicity,behavior analysis,smoking event detection,hand-held object detection,code book,interaction event
Code book,Computer vision,Object detection,Histogram,Pattern recognition,Brute-force search,Computer science,Mobile device,Artificial intelligence,Code (cryptography),Event analysis
Journal
Volume
Issue
ISSN
25
6
1047-3203
Citations 
PageRank 
References 
0
0.34
33
Authors
5
Name
Order
Citations
PageRank
Jun-Wei Hsieh175167.88
Jiun-Cheng Cheng2132.67
Li-Chih Chen3555.37
Chi-Hung Chuang4479.06
Duan-Yu Chen529628.79