Visual tracking of high DOF articulated structures: an application to human hand tracking
ECCV '94 Proceedings of the third European conference on Computer Vision (Vol. II)
An Appearance-Based Framework for 3D Hand Shape Classification and Camera Viewpoint Estimation
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Analyzing and Capturing Articulated Hand Motion in Image Sequences
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real Time Search for Similar Hand Images from Database for Robotic Hand Control
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Realtime Hand Posture Estimation with Self-Organizing Map for Stable Robot Control
IEICE - Transactions on Information and Systems
Features extraction from hand images based on new detection operators
Pattern Recognition
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Previous systems for human hand posture estimation have adopted clustered multi-layer large-scale database with narrowing of search space by its past estimation results. But once an estimated result at a time is out of the search space, the system can't find out a true or optimal value. Our system therefore has adopted non-clustered large-scale database including narrowing of search space, rather, a coarse search at the first stage according to some aspects of inputted hand images, and an accurate search at the second stage with low-order image features. The experimental results showed that the averaged estimation error is -2.11 degrees, and the candidates for accurate search at the second stage are reduced from 28, 386 to 137.7 data sets, including our system realizes the stable hand posture estimation with high accuracy and processing speed as previous system without using the past results.