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Appearance-Based Gesture Recognition in The Compressed Domain - Poster

Citation Author(s):
Anvesha Amaravati, Justin Romberg, Arijit Raychowdhury
Submitted by:
Shaojie Xu
Last updated:
2 March 2017 - 12:12pm
Document Type:
Poster
Document Year:
2017
Event:
Presenters:
Kyle Xu
Paper Code:
2919

Abstract

We propose a novel appearance-based gesture recognition algorithm using compressed domain signal processing tech- niques. 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.

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