• Action recognition via sequence embedding 

    Gong, Wei (University of Missouri--Columbia, 2011)
    [ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] A comb structural exemplar embedding based approach is introduced for action recognition. We propose a new framework to represent an action as a weak ...
  • Object detection with large intra-class variation 

    Chen, Guang (University of Missouri--Columbia, 2011)
    For object detection, the state-of-the-art performance is achieved through supervised learning. The performances of object detectors of this kind are mainly determined by two factors: features and underlying classification ...
  • Visual recognition using hybrid camera 

    Tang, Shuai (University of Missouri--Columbia, 2011)
    Visual recognition is an exciting but difficult task. Recent dramatic advance in compute vision technology has made some promising progress. For example, the launch of hybrid camera provides both RGB and depth information ...