Hand Posture Estimation by Combining 2-D Appearance-Based and 3-D Model-Based Approaches
نویسندگان
چکیده
This paper proposes a method for the rapid and precise estimation of human hand postures by combining 2-D appearance matching and 3-D model-based fitting. First a rough posture estimate is obtained by image indexing. Each possible hand appearance generated from a given 3-D shape model is labeled by an index obtained by PCA compression and registered with its 3-D model parameters in advance. By retrieving the index of the input image, the method can obtain the matched appearance image and its 3-D parameters rapidly. Then, starting from the obtained rough estimate, it estimates the posture and moreover refines the given initial 3-D model by model-fitting. The sequential activation of the two processes in every frame gives the precise posture estimate rapidly. The effectiveness of the method is shown by experimental results.
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