With the massive number of cameras have been widely
deployed in past few years, human activity analysis
has attracted great interest from computer vision
researchers and become a hot research area due to its
promising applications in many areas such as
automated visual surveillance, computer-human
interactions, and motion-based identification and
diagnosis. However, to detect, categorize and
recognize human activity from video is a complicate
and difficult problem.
This book presents techniques in two topics: general
human activity recognition and human activity
analysis for the purpose of identifying pathological
gait based on symmetry analysis. This book should
help shed some light on this research area, and
should be especially useful to professionals working
in this field, or anyone else who may be considering
utilizing video for human activity analysis.
Feng Niu received the Ph.D. degrees in ECE. from University of
Miami, USA, in 2007. He has published many journal and
conference papers and filed two patents. His present research
interests include image/video analysis, pattern recognition,
machine learning and analytical modeling. He has been an active
member in SME and IEEE.