This work aims at automatically recognizing sequences of complex karate movements and giving a measure of the quality of the movements performed. Since this is a problem which intrinsically needs a 3D model, we propose a solution taking as input sequences of skeletal motions that can derive from both motion capture hardware or consumer-level, off the shelf, depth sensing systems. The proposed system is constituted by four different modules: skeleton representation, pose classification, temporal alignment, and scoring. The proposed system is tested on a set of different punch, kick and defense karate moves executed starting from the simplest case, i.e. fixed static stances (heiko dachi) up to sequences in which the starting stances is different from the ending one. The dataset has been recorded using a single Microsoft Kinect. The dataset includes the recordings of both male and female athletes with different skill levels, ranging from novices to masters.
Publications
1.
Karate moves recognition from skeletal motion
(Simone Bianco, Francesco Tisato)
In Three-Dimensional Image Processing (3DIP) and Applications 2013, volume 8650, pp. 86500K, SPIE, 2013.
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BibTex
Doi
@inproceedings{bianco2013karate-moves,
author = {Bianco, Simone and Tisato, Francesco},
year = {2013},
pages = {86500K},
title = {Karate moves recognition from skeletal motion},
volume = {8650},
publisher = {SPIE},
booktitle = {Three-Dimensional Image Processing (3DIP) and Applications 2013},
pdf = {/download/bianco2013karate-moves.pdf},
doi = {10.1117/12.2006229}}
