Face detection and tracking for intent recognition

Abstract

An algorithm for visual intent recognition based on adaptive boosting and principal components analysis is presented, with two different motions of the human face namely rotation and vertical motion as intent indicators. The context for which this solution is intended is that of wheelchair bound individuals who want to travel in a certain direction through their face in rotation, and to go forward and stop through their face in vertical motion. The approach is based on the work of Jia and Hu [1], [2], where instead of inferring intention as they proposed through head pose estimation on a single frame, the face in motion is represented using an intention curve that is subsequently classified for intent recognition through a decision rule. This work intends to provide a contribution to the realization of an enabled environment allowing people with severe disabilities and the elderly to be more independent and active in society.