Combination of accumulated motion and color segmentation for human activity analysis
Journal on Image and Video Processing - Anthropocentric Video Analysis: Tools and Applications
Decision making in assistive environments using multimodal observations
Proceedings of the 2nd International Conference on PErvasive Technologies Related to Assistive Environments
My Tai-Chi book: a virtual-physical social network platform
Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks
Human action recognition using multiple views: a comparative perspective on recent developments
J-HGBU '11 Proceedings of the 2011 joint ACM workshop on Human gesture and behavior understanding
The human motion database: A cognitive and parametric sampling of human motion
Image and Vision Computing
Instructing people for training gestural interactive systems
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A survey of video datasets for human action and activity recognition
Computer Vision and Image Understanding
Vision-based arm gesture recognition for a long-range human---robot interaction
The Journal of Supercomputing
ChAirGest: a challenge for multimodal mid-air gesture recognition for close HCI
Proceedings of the 15th ACM on International conference on multimodal interaction
A template matching approach of one-shot-learning gesture recognition
Pattern Recognition Letters
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This paper presents a full-body gesture database which contains 2D video data and 3D motion data of 14 normal gestures, 10 abnormal gestures and 30 command gestures for 20 subjects. We call this database the Korea University Gesture(KUG) database. Using 3D motion cameras and 3 sets of stereo cameras, we captured 3D motion data and 3 pairs of stereo-video data at 3 different directions for normal and abnormal gestures. In case of command gestures, 2 pairs of stereo-video data is obtained by 2 sets of stereo cameras with different focal length in order to effectively capture views of whole body and upper body, simultaneously. In addition to these, the 2D silhouette data is synthesized by separating a subject and background in 2D stereo-video data and saved as binary mask images. In this paper, we describe the gesture capture system, the organization of database, the potential usages of the database and the way of obtaining the KUG database.