Mitsubishi Electric Research Laboratories

Michael Jones

MERL Research / Technical Staff
Senior Principal Technical Staff
Ph.D., Massachusetts Institute of Technology, 1997

Phone: (617) 621 7587
Email:



Mike Jones joined MERL in the fall of 2001 after 4 years at the Digital/Compaq Cambridge Research Laboratory. Mike's main area of interest is computer vision, and he is particularly interested in using machine-learning approaches for solving computer vision problems. He has focused on algorithms for detecting and analyzing people in images and video such as face detection, skin detection and facial analysis using morphable models. Recent Projects include Fast Face Detection using a Cascade of Detectors.

Publications:

Jones, M.; Snow, D., "Pedestrian Detection Using Boosted Features Over Many Frames", International Conference on Pattern Recognition (ICPR), Motion, Tracking, Video Analysis, December 2008 (ICPR 2008, TR2008-027)

Pelosof, R.; Jones, M.; Vovsha, I.; Rudin, C., "Online Coordinate Boosting", The Smithsonian/NASA Astrophysics Data System, ARXIV Statistics - Machine Learning, October 2008 (eprint arXiv:0810.4553, TR2008-069)

Viola, P.; Jones, M.J.; Snow, D., "Detecting Pedestrians Using Patterns of Motion and Appearance", IEEE International Conference on Computer Vision (ICCV), Vol. 2, pp. 734-741, October 2003 (IEEE Xplore, TR2003-090)

Viola, P.; Jones, M., "Rapid Object Detection Using a Boosted Cascade of Simple Features", IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), ISSN: 1063-6919, Vol. 1, pp. 511-518, December 2001 (IEEE Xplore, TR2004-043)

Technical Reports:

TR2009-023 Face Recognition: Where We Are and Where To Go From Here
TR2007-074 A New Weak Learning Algorithm for Real Hyperplane Features Applied to Face Detection
TR2005-044 A System for Automatic Iris Capturing
TR2003-128 Fast Pose Estimation with Parameter-Sensitive Hashing
TR2003-127 Unsupervised Improvement of Visual Detectors Using Co-Training
TR2003-096 Fast Multi-view Face Detection
TR2003-025 Face Recognition Using Boosted Local Features