Segment-Based Hand Pose Estimation

The work presented here solves two major problems of hand pose recognition: (A) determining what pose is shown in a given, input picture and (B) detecting the presence of a known input pose in a given input video. It builds on the earlier work of Athitsos and Sclaroff [1] toward solving Problem A. Because that method relies upon lines found in the input data and requires computergenerated database models, it is unsuitable for the later, video problem. Our reworking of this framework uses different, region-based information to allow video frames to be used as the “database” in which to look for the test pose. It returns database images of hands in the same configuration as a query image by using a series of steps based on the number and direction of visible finger protrusions, Chamfer distance, orientation histograms, and a competitive, comparison-based matching of each visible finger segment. Detailed result data demonstrates the system’s feasibility and potential.

• Type: Conference
• Year: 2005
• Where: CRV
• Authors: Christopher Schwarz, Niels da Vitoria Lobo
• Keywords: CRV 2005, Hand Pose Recognition, Input, Input Pose, Robotics