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.
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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.
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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.
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Embedded Computer Vision, exemplified by the migration from powerful workstations to embedded processors in computer vision applications, is a new and emerging field that enables an associated shift in application development and implementation. This comprehensive volume brings together a wealth of experiences from leading researchers in the field of embedded computer vision, from both academic and industrial research centers, and covers a broad range of challenges and trade-offs brought about by this paradigm shift. Part I provides an exposition of basic issues and applications in the area necessary for understanding the present and future work. Part II offers chapters based on the most recent research and results. Finally, the last part looks ahead, providing a sense of what major applications could be expected in the near future, describing challenges in mobile environments, video analytics, and automotive safety applications. Features: • Discusses the lateststate-of-the-art techniques in embedded computer vision • Presents a thorough introductory section on hardware and architectures, design methodologies, and video analytics to aid the reader’s understanding through the following chapters • Offers emphasis on tackling important problems for society, safety, security, health, mobility, connectivity, and energy efficiency • Discusses evaluation of trade-offs required to design cost-effective systems for successful products • Explores the advantages of various architectures, development of high-level software frameworks and cost-effective algorithmic alternatives • Examines issues of implementation on fixed-point processors, presented through an example of an automotive safety application • Offers insights from leaders in the field on what future applications will be This book is a welcome collection of stand-alone articles, ideal for researchers, practitioners, and graduate students. It provides historical perspective, the latest research results, and a vision for future developments in the emerging field of embedded computer vision. Supplementary material can be found at http://www.embeddedvisioncentral.com.
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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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Provides historical perspective, the latest research results and a vision for future developments in this new field of embedded computer vision Contains high-level, state-of-the-art research results Looks ahead, providing a sense of what major applications could be expected in the near future
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Produktdetaljer

ISBN
9781849967761
Publisert
2010-10-21
Utgiver
Vendor
Springer London Ltd
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, P, 06
Språk
Product language
Engelsk
Format
Product format
Heftet