Robust hand tracking in low-resolution video sequences

Authors:
Nyan Bo Bo;Matthew N. Dailey;Bunyarit Uyyanonvara
Affiliations:
Sirindhorn International Institute of Technology, Thammasat University, Klong Luang, Pathumthani, Thailand;Computer Science and Information Management, Asian Institute of Technology, Klong Luang, Pathumthani, Thailand;Sirindhorn International Institute of Technology, Thammasat University, Klong Luang, Pathumthani, Thailand
Venue:
ACST'07 Proceedings of the third conference on IASTED International Conference: Advances in Computer Science and Technology
Year:
2007

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Abstract

Automatic detection and tracking of human hands in video imagery has many applications. While some success has been achieved in human-computer interaction applications, hand tracking would also be extremely useful in security systems, where it could help the system to understand and predict human actions, intentions, and goals. We have designed and implemented a prototype hand tracking system, which is able to track the hands of moving humans in low resolution video sequences. Our system uses grayscale appearance and skin color information to classify image sub-windows as either containing or not containing a human hand. The prototype's performance is quite promising, detecting nearly all visible hands in a test sequence with a relatively low error rate. In future work we plan to improve the prototype and explore methods for interpreting human gestures in surveillance video.