An Overview of Contest on Semantic Description of Human Activities (SDHA) 2010

• Published in: Recognizing Patterns in Signals, Speech, Images and Videos pp. 270 - 285
• Main Authors: Ryoo, M. S., Chen, Chia-Chih, Aggarwal, J. K., Roy-Chowdhury, Amit
• Format: Book Chapter
• Language: English; Japanese
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 2010
• Series: Lecture Notes in Computer Science
• Subjects: Activity recognition contest; human activity recognition; video analysis
• ISBN: 9783642177101; 3642177107
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-642-17711-8_28

This paper summarizes results of the 1st Contest on Semantic Description of Human Activities (SDHA), in conjunction with ICPR 2010. SDHA 2010 consists of three types of challenges, High-level Human Interaction Recognition Challenge, Aerial View Activity Classification Challenge, and Wide-Area Activity Search and Recognition Challenge. The challenges are designed to encourage participants to test existing methodologies and develop new approaches for complex human activity recognition scenarios in realistic environments. We introduce three new public datasets through these challenges, and discuss results of the state-of-the-art activity recognition systems designed and implemented by the contestants. A methodology using a spatio-temporal voting [19] successfully classified segmented videos in the UT-Interaction datasets, but had a difficulty correctly localizing activities from continuous videos. Both the method using local features [10] and the HMM based method [18] recognized actions from low-resolution videos (i.e. UT-Tower dataset) successfully. We compare their results in this paper.