M. Grundmann, F. Meier, I. Essa
3D Shape Context and Distance Transform for Action RecognitionInternational Conference on Pattern Recogntion (ICPR), Tampa, FL, December 2008

We propose the use of 3D (2D+time) Shape Context to recognize the spatial in human actions. We represent an action in a video sequence by a 3D point silhouettes over time. A non-uniform sampling method is pintroduced that parts using a Euclidean 3D Distance Transform. Actions are then classified by matching the extracted point clouds. Our proposed approach is based on a global matching and does not require specific training to learn the model. We test the approach thoroughly on two publicly available datasets and compare to several state-of-the-art methods. The achieved classification accuracy is on par with or superior to the best results reported to date.

Bibtex entry

@INPROCEEDINGS{Grundmann08,
author = {M. Grundmann and F. Meier and I. Essa },
title = {3D Shape Context and Distance Transform for Action Recognition},
booktitle = {ICPR},
year = {2008},
}