We propose a novel appearance-based gesture recognition algorithm using compressed domain signal processing techniques. Gesture features are extracted directly from the compressed measurements, which are the block averages and the coded linear combinations of the image sensor's pixel values. We also improve both the computational efficiency and the memory requirement of the previous DTW-based K-NN gesture classifiers. Both simulation testing and hardware implementation strongly support the proposed algorithm.
@article{arxiv.1903.00100,
title = {Appearance-based Gesture recognition in the compressed domain},
author = {Shaojie Xu and Anvesha Amaravati and Justin Romberg and Arijit Raychowdhury},
journal= {arXiv preprint arXiv:1903.00100},
year = {2019}
}
Comments
arXiv admin note: text overlap with arXiv:1605.08313