Dr. Robert P. Loce
Research Fellow, Technical Manager at Datto Inc
SPIE Involvement:
Fellow status | Conference Chair | Conference Program Committee | Author | Editor | Instructor
Area of Expertise:
Image Processing , Computer Vision , Video Processing , Intellectual Property , Imaging Systems
Profile Summary

Robert Loce is a Research Fellow and Technical Manager in the Xerox Research Center Webster. He joined Xerox in 1981 with an Associate degree in Optical Engineering Technology from Monroe Community College. While working in optical and imaging technology and research departments at Xerox, he received a BS in Photographic Science (RIT 1985), an MS in Optical Engineering (UR 1987), a PhD in Imaging Science (RIT 1993), and passed the US Patent Bar (2002). A significant portion of his earlier career was devoted to development of image processing methods for color electronic printing. His current research activities involve leading an organization and projects into new computer vision and video technologies that are relevant to transportation, healthcare,retail, and surveillance. He has publications and many patents in the areas of digital image processing, image enhancement, imaging systems, optics and halftoning. He is a Fellow of SPIE and a Senior Member of IEEE. His publications include a book on enhancement and restoration of digital documents, and book chapters on digital halftoning and digital document processing. He is currently an associate editor for Journal of Electronic Imaging, and has been an associate editor for Real-Time Imaging, and IEEE Transactions on Image Processing.
Publications (50)

SPIE Journal Paper | October 27, 2017
JEI Vol. 26 Issue 05
KEYWORDS: Video surveillance, Video, Safety, Analytics, Cameras, Surveillance, Content addressable memory, Imaging systems, Information security, Heat treatments

SPIE Journal Paper | July 20, 2017
JEI Vol. 26 Issue 05
KEYWORDS: Video surveillance, Video, Content addressable memory, Neural networks, Surveillance, Cameras, Convolution

SPIE Conference Volume | March 12, 2015

PROCEEDINGS ARTICLE | March 4, 2015
Proc. SPIE. 9407, Video Surveillance and Transportation Imaging Applications 2015
KEYWORDS: Cameras, Calibration, Error analysis, Roads, Motion detection, Motion estimation, Video, Ions, Detection and tracking algorithms, LIDAR

PROCEEDINGS ARTICLE | March 4, 2015
Proc. SPIE. 9407, Video Surveillance and Transportation Imaging Applications 2015
KEYWORDS: Cell phones, Imaging systems, Cameras, Machine learning, Sensors, Near infrared, Image classification, Visualization, Facial recognition systems, Safety

Showing 5 of 50 publications
Conference Committee Involvement (5)
Video Surveillance and Transportation Imaging Applications 2015
10 February 2015 | San Francisco, California, United States
Video Surveillance and Transportation Imaging Applications 2014
3 February 2014 | San Francisco, California, United States
Visual Information Processing and Communication IV
6 February 2013 | Burlingame, California, United States
Video Surveillance and Transportation Imaging Applications
4 February 2013 | Burlingame, California, United States
Visual Information Processing and Communication III
24 January 2012 | Burlingame, California, United States
Course Instructor
SC1131: Computer Vision and Imaging in Transportation Applications
This course introduces the attendee to applications in the transportation industry that employ imaging, computer vision, and video processing technologies. The class begins with a survey of key topics in transportation falling under three broad categories: safety, efficiency, and security. Topics include driver assistance, traffic surveillance and law enforcement, video-based tolling, monitoring vehicles of interest, and incident detection. The second part of the course provides a more in-depth treatment of state-of-art approaches to selected problems such as vehicle license plate recognition, vehicle occupancy estimation, speed enforcement, driver attention monitoring, and sensing of road and environmental conditions. Where necessary, background material on relevant computer vision concepts will be covered, such as image segmentation, object detection, classification, recognition, and tracking, and 3D camera geometry.
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