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Titlebook: Embedded Computer Vision; Branislav Kisačanin,Shuvra S. Bhattacharyya,Sek Ch Book 2009 Springer-Verlag London 2009 Automotive Safety.Compu

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发表于 2025-3-21 16:04:56 | 显示全部楼层 |阅读模式
书目名称Embedded Computer Vision
编辑Branislav Kisačanin,Shuvra S. Bhattacharyya,Sek Ch
视频video
概述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.L
丛书名称Advances in Computer Vision and Pattern Recognition
图书封面Titlebook: Embedded Computer Vision;  Branislav Kisačanin,Shuvra S. Bhattacharyya,Sek Ch Book 2009 Springer-Verlag London 2009 Automotive Safety.Compu
描述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
出版日期Book 2009
关键词Automotive Safety; Computer Vision; Driver Assistance; Embedded Computer Vision; Embedded Systems; Patter
版次1
doihttps://doi.org/10.1007/978-1-84800-304-0
isbn_softcover978-1-84996-776-1
isbn_ebook978-1-84800-304-0Series ISSN 2191-6586 Series E-ISSN 2191-6594
issn_series 2191-6586
copyrightSpringer-Verlag London 2009
The information of publication is updating

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发表于 2025-3-21 20:29:47 | 显示全部楼层
Using Robust Local Features on DSP-Based Embedded Systemsy stable extremal regions) detector as well as the PCA-SIFT descriptor, and discuss their suitability for smart systems for camera calibration and object recognition tasks. The second contribution of this work is the experimental evaluation of these methods on two challenging tasks, namely, the task
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Wachstum und Tod von Mikroorganismen,from which a vision system might be realized. Component-to-component relationships, data and control pathways, and signaling methods between and among these components are discussed, and specific organizational approaches are compared and contrasted.
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https://doi.org/10.1007/978-3-662-00502-6f OpenVL is to allow users to quickly and easily recover useful information from multiple scenes, in a cross-platform, cross-language manner across various software environments and hardware platforms. To validate the critical underlying concepts of OpenVL, a human tracking system and a local positi
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Book 2009ner...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
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Wachstum und Tod von Mikroorganismen,on pipeline from image acquisition to result output, including the operations that are to be performed on the images. This chapter gives an overview of this pipeline and the involved hardware components. It discusses several types of image sensors as well as their readout styles, speeds, and interfa
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