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Kisacanin / Chai / Bhattacharyya

Embedded Computer Vision

Medium: Buch
ISBN: 978-1-84996-776-1
Verlag: Springer
Erscheinungstermin: 21.10.2010
Lieferfrist: bis zu 10 Tage
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.

Produkteigenschaften


  • Artikelnummer: 9781849967761
  • Medium: Buch
  • ISBN: 978-1-84996-776-1
  • Verlag: Springer
  • Erscheinungstermin: 21.10.2010
  • Sprache(n): Englisch
  • Auflage: 1. Auflage. Softcover version of original hardcover Auflage 2009
  • Serie: Advances in Computer Vision and Pattern Recognition
  • Produktform: Kartoniert, Paperback
  • Gewicht: 476 g
  • Seiten: 284
  • Format (B x H x T): 155 x 235 x 17 mm
  • Ausgabetyp: Kein, Unbekannt

Autoren/Hrsg.

Herausgeber

Kisacanin, Branislav

Chai, Sek

Bhattacharyya, Shuvra S.

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.