Robot PAL Lab Meeting (Casey): Fast and Accurate Hand Pose Detection for Human-Robot Interaction

Title: Fast and Accurate Hand Pose Detection for Human-Robot Interaction
Author: Luis Antón-Canalís1, Elena Sánchez-Nielsen, and Modesto Castrillón-Santana
From: IbPRIA 2005, LNCS 3522, pp. 553–560, 2005

Abstract: Enabling natural human-robot interaction using computer vision
based applications requires fast and accurate hand detection. However, previous
works in this field assume different constraints, like a limitation in the number
of detected gestures, because hands are highly complex objects difficult to locate.
This paper presents an approach which integrates temporal coherence cues
and hand detection based on wrists using a cascade classifier. With this approach,
we introduce three main contributions: (1) a transparent initialization
mechanism without user participation for segmenting hands independently of
their gesture, (2) a larger number of detected gestures as well as a faster training
phase than previous cascade classifier based methods and (3) near real-time performance
for hand pose detection in video streams.
1 Introduction
Improving human-robot interaction has been an active research field