Overview

As a graduate student at Ohio State in the mid-1970s, I inherited a unique c- puter vision laboratory from the doctoral research of previous students. They had designed and built an early frame-grabber to deliver digitized color video from a (very large) electronic video camera on a tripod to a mini-computer (sic) with a (huge!) disk drive—about the size of four washing machines. They had also - signed a binary image array processor and programming language, complete with a user’s guide, to facilitate designing software for this one-of-a-kindprocessor. The overall system enabled programmable real-time image processing at video rate for many operations. I had the whole lab to myself. I designed software that detected an object in the eldofview,trackeditsmovementsinrealtime,anddisplayedarunningdescription of the events in English. For example: “An object has appeared in the upper right corner...Itismovingdownandtotheleft...Nowtheobjectisgettingcloser...The object moved out of sight to the left”—about like that. The algorithms were simple, relying on a suf cient image intensity difference to separate the object from the background (a plain wall). From computer vision papers I had read, I knew that vision in general imaging conditions is much more sophisticated. But it worked, it was great fun, and I was hooked.

Full Product Details

Author:   Branislav Kisacanin ,  Shuvra S. Bhattacharyya ,  Sek Chai
Publisher:   Springer London Ltd
Imprint:   Springer London Ltd
Edition:   Softcover reprint of hardcover 1st ed. 2009
Dimensions:   Width: 15.50cm , Height: 1.60cm , Length: 23.50cm
Weight:   0.480kg
ISBN:  

9781849967761

ISBN 10:   1849967768
Pages:   284
Publication Date:   21 October 2010
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

Hardware Considerations for Embedded Vision Systems.- Design Methodology for Embedded Computer Vision Systems.- We Canwatch It For You Wholesale.- Advances in Embedded Computer Vision.- Using Robust Local Features on DSP-Based Embedded Systems.- Benchmarks of Low-Level Vision Algorithms for DSP, FPGA, and Mobile PC Processors.- SAD-Based Stereo Matching Using FPGAs.- Motion History Histograms for Human Action Recognition.- Embedded Real-Time Surveillance Using Multimodal Mean Background Modeling.- Implementation Considerations for Automotive Vision Systems on a Fixed-Point DSP.- Towards OpenVL: Improving Real-Time Performance of Computer Vision Applications.- Looking Ahead.- Mobile Challenges for Embedded Computer Vision.- Challenges in Video Analytics.- Challenges of Embedded Computer Vision in Automotive Safety Systems.

Reviews

From the reviews: The book is a result of the Embedded Computer Vision Workshop 2007. ! provides a very good overview of the current state of the art in embedded computer vision and of the major trends and growing markets. ! it is a good start and provides an extensive list of references to look for if one wants to go into more detail. Overall I would recommend this book to anyone interested in getting into this exciting field. (Marcus E. Hennecke, IAPR Newsletter, Vol. 33 (2), April, 2011)

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