Title: Comprehensive analysis of a diverse group of features and development of vision-based two-level hand detector under practical environment conditions

Authors: Songhita Misra; Rabul Hussain Laskar

Addresses: Aditya Engineering College (A), Surampelam-533437, Andhra Pradesh, India ' Department of ECE, NIT Silchar, Silchar-788010, Assam, India

Abstract: Developing a bare-hand detection system for practical environment conditions is a complex and challenging task. Factors such as change in appearance, uneven illumination, and complex background add up to the difficulty in detecting the target hand. Present study newly explored 13 colour-texture and integrates them with texture models to develop robust two-level hand detector under practical conditions mentioned above. Colour-texture and texture models are assessed using multiple classification tools and employed in two subsequent levels such that the second level only classifies the optimal sub-windows classified in the first level. The analysis showed that the proposed two-level detection system detects the hand with 53.4% higher accuracy than the baseline model which the integrated motion detection and skin filtering method, under the practical conditions. With five times lower time-complexity than the baseline model, the proposed system can be used to detect hand in both static as well as dynamic gesture systems.

Keywords: two-level hand detection system; complex background; positional variation; rotation variation; uneven illumination; AdaBoost classifier; naïve Bayes; support vector machine; colour-texture features.

DOI: 10.1504/IJCVR.2021.113399

International Journal of Computational Vision and Robotics, 2021 Vol.11 No.2, pp.175 - 200

Received: 13 Sep 2018
Accepted: 06 Sep 2019
Published online: 03 Mar 2021 *

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