A Trainable System for Object Detection
International Journal of Computer Vision - special issue on learning and vision at the center for biological and computational learning, Massachusetts Institute of Technology
Trinocular Active Range-Sensing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Tracking of Moving Heads in Cluttered Scenes from Stereo Vision
RobVis '01 Proceedings of the International Workshop on Robot Vision
Head Detection and Tracking by 2-D and 3-D Ellipsoid Fitting
CGI '00 Proceedings of the International Conference on Computer Graphics
A Four-step Camera Calibration Procedure with Implicit Image Correction
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Real-Time, 3D Estimation of Human Body Postures from Trinocular Images
MPEOPLE '99 Proceedings of the IEEE International Workshop on Modelling People
3-D model-based tracking of human upper body movement: a multi-view approach
ISCV '95 Proceedings of the International Symposium on Computer Vision
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Head detection is an important, but difficult task, if no restrictions such as static illumination, frontal face appearance or uniform background can be assumed. We present a system that is able to perform head detection under very general conditions by employing a 3D measurement system namely a structured light distance measurement. An algorithm of head detection from sparse 3D data (19脳19 data points) is developed that reconstructs a 3D surface over the image plane and detects head hypotheses of ellipsoidal shape. We demonstrate that detection and rough localization is possible in up to 90% of the images.