Prop-free pointing detection in dynamic cluttered environments

Abstract—Vision-based prop-free pointing detection is challenging both from an algorithmic and a systems standpoint. From a computer vision perspective, accurately determining where multiple users are pointing is difficult in cluttered environments with dynamic scene content. Standard approaches relying on appearance models or background subtraction to segment users operate poorly in this domain. We propose a method that focuses on motion analysis to detect pointing gestures and robustly estimate the pointing direction. Our algorithm is self-initializing; as the user points, we analyze the observed motion from two cameras and infer rotation centers that best explain the observed motion. From these, we group pixel-level flow into dominant pointing vectors that each originate from a rotation center and merge across views to obtain 3D pointing vectors. However, our proposed algorithm is computationally expensive, posing systems challenges even with current computing infrastructure. We...

• Type: Journal
• Year: 2011
• Where: FGR
• Authors: Pyry Matikainen, Padmanabhan Pillai, Lily B. Mummert, Rahul Sukthankar, Martial Hebert
• Keywords: Abstract—Vision-based Prop-free Pointing, Biometrics, FGR 2011, Pointing Vectors, Rotation Center