Methods and Algorithms for Human Detection in Video Sequences

Lower prices of video sensors, security concerns and the need for better and faster
algorithms to extract high level information from video sequences are all factors which
have stimulated research in the area of automated video surveillance systems. In the
context of security the analysis of human interrelations and their environment provides
hints to proactively identify anomalous behavior. However, human detection is a
necessary component in systems where the automatic extraction of higher level
information, such as recognizing individuals' activities, is required. The human detection
problem is one of classification. In general, motion, appearance and shape are the
classification approaches a system can employ to perform human detection. Techniques
representative of these approaches, such us periodic motion detection, skin color
detection and MPEG-7 shape descriptors are implemented in this work. An infrastructure
that allows data collection for such techniques was also implemented.