Abstract
Benchmarking
methods for 3d hand tracking is still an open problem due to the
difficulty of acquiring ground truth data. We introduce a new dataset
and benchmarking protocol that is insensitive to the accumulative error
of other protocols. To this end, we create testing frame pairs of
increasing difficulty and measure the pose estimation error separately
for each of them. This approach gives new insights and allows to
accurately study the performance of each feature or method without
employing a full tracking pipeline. Following this protocol, we
evaluate various directional distances in the context of
silhouette-based 3d hand tracking, expressed as special cases of a
generalized Chamfer distance form. An appropriate parameter setup is
proposed for each of them, and a comparative study reveals the best
performing method in this context.
Publications
Tzionas
D. and Gall J.
A Comparison of Directional Distances for Hand Pose Estimation (PDF, BibTex)
German Conference on Pattern Recognition (GCPR'13)
Supplementary Material: A Comparison of Directional Distances for Hand Pose Estimation (PDF)
A Comparison of Directional Distances for Hand Pose Estimation (PDF, BibTex)
German Conference on Pattern Recognition (GCPR'13)
Supplementary Material: A Comparison of Directional Distances for Hand Pose Estimation (PDF)
Video
Data
Dataset
+ Viewer, 5.0 GB, (current version requires resolution
2560x1440 resolution)
ReadMe file, 2.0 MB, (also included in the above file)
ReadMe file, 2.0 MB, (also included in the above file)
Related projects
Capturing Hand Motion with an RGB-D Sensor, Fusing a Generative Model with Salient Points, GCPR 2014. Link
Citation
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Contact
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