Hand Pointing Detection Using Live Histogram Template of Forehead Skin

TL;DR

This paper presents a real-time hand pointing detection method using forehead skin histograms in HSV space, enabling accurate fingertip and pointing vector detection from standard webcams.

Contribution

A novel approach utilizing forehead skin histogram templates and contour analysis for live hand pointing detection in 2D space.

Findings

Achieved 94% true positive rate in detection.

Achieved 85% true negative rate in detection.

Effective in live video from common webcams.

Abstract

Hand pointing detection has multiple applications in many fields such as virtual reality and control devices in smart homes. In this paper, we proposed a novel approach to detect pointing vector in 2D space of a room. After background subtraction, face and forehead is detected. In the second step, forehead skin H-S plane histograms in HSV space is calculated. By using these histogram templates of users skin, and back projection method, skin areas are detected. The contours of hand are extracted using Freeman chain code algorithm. Next step is finding fingertips. Points in hand contour which are candidates for the fingertip can be found in convex defects of convex hull and contour. We introduced a novel method for finding the fingertip based on the special points on the contour and their relationships. Our approach detects hand-pointing vectors in live video from a common webcam with 94%TP and 85%TN.