Title :
Illumination invariant head pose estimation using single camera
Author :
Nanda, Harsh ; FujiMura, Kikuo
Author_Institution :
Dept. of Comput. Sci., Maryland Univ., College Park, MD, USA
Abstract :
A learning based approach is presented for a single camera based robust head pose estimation in highly cluttered and complex real world environments. The method makes effective use of a recently introduced real-time 3D depth sensing technology, resulting in illumination-invariant head pose estimation. The main target application of our work is to classify the focus of attention of an automobile driver as straight-ahead, towards-rear-view mirror, towards the dash board, etc. This type of information is expected to be useful in conjunction with other sensors to enable safer driving.
Keywords :
automobiles; computer vision; image recognition; learning by example; neural nets; principal component analysis; real-time systems; 3D depth sensing technology; attention focus; automobile driver; complex real world environments; dash board; head pose estimation; illumination invariant; learning based approach; neural nets; principal component analysis; real time technology; rear view mirror; Cameras; Face detection; Focusing; Head; Infrared sensors; Layout; Lighting; Neural networks; Principal component analysis; Training data;
Conference_Titel :
Intelligent Vehicles Symposium, 2003. Proceedings. IEEE
Print_ISBN :
0-7803-7848-2
DOI :
10.1109/IVS.2003.1212950
