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Titlebook: Exploratory Vision; The Active Eye Michael S. Landy,Laurence T. Maloney,Misha Pavel Book 1996 Springer-Verlag New York, Inc. 1996 Computer

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發(fā)表于 2025-3-21 16:19:21 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Exploratory Vision
副標(biāo)題The Active Eye
編輯Michael S. Landy,Laurence T. Maloney,Misha Pavel
視頻videohttp://file.papertrans.cn/320/319451/319451.mp4
叢書名稱Springer Series in Perception Engineering
圖書封面Titlebook: Exploratory Vision; The Active Eye Michael S. Landy,Laurence T. Maloney,Misha Pavel Book 1996 Springer-Verlag New York, Inc. 1996 Computer
描述Advances in sensing, signal processing, and computer technology during the past half century have stimulated numerous attempts to design general-purpose ma- chines that see. These attempts have met with at best modest success and more typically outright failure. The difficulties encountered in building working com- puter vision systems based on state-of-the-art techniques came as a surprise. Perhaps the most frustrating aspect of the problem is that machine vision sys- tems cannot deal with numerous visual tasks that humans perform rapidly and effortlessly. In reaction to this perceived discrepancy in performance, various researchers (notably Marr, 1982) suggested that the design of machine-vision systems should be based on principles drawn from the study of biological systems. This "neuro- morphic" or "anthropomorphic" approach has proven fruitful: the use of pyramid (multiresolution) image representation methods in image compression is one ex- ample of a successful application based on principles primarily derived from the study of biological vision systems. It is still the case, however, that the perfor- of computer vision systems falls far short of that of the natural systems m
出版日期Book 1996
關(guān)鍵詞Computer Vision; Performance; Picking; Shading; Simulation; Stereo; machine vision
版次1
doihttps://doi.org/10.1007/978-1-4612-3984-0
isbn_softcover978-1-4612-8460-4
isbn_ebook978-1-4612-3984-0Series ISSN 1431-858X
issn_series 1431-858X
copyrightSpringer-Verlag New York, Inc. 1996
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1431-858X eral-purpose ma- chines that see. These attempts have met with at best modest success and more typically outright failure. The difficulties encountered in building working com- puter vision systems based on state-of-the-art techniques came as a surprise. Perhaps the most frustrating aspect of the pr
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Henry More and the Scientific Revolution,r, we show that the use of a hemispherical (retinal) imaging surface combined with the active process of fixation generates an optical flow field of a particularly simple form. A further contribution is the finding that the sign of retinal flow at the retinal periphery can be used to predict collisions.
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https://doi.org/10.1007/978-3-030-31650-1t cognitive activities, helping ensure that the eye will be directed to objects of current interest with little or no additional effort on the part of the observer. Cognitive control of eye movements, which is so prominent in human beings, may also be a useful principle to apply to the design of robots.
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Henry James‘ Narrative Technique formulated using robust regression methods. The nature of errors in visual signals will be discussed, and a prescription for formulating robust algorithms will be described. To illustrate the concepts, robust methods have been applied to three problems: surface reconstruction, image flow estimation, and dynamic stereo.
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Heparanase?– Discovery and Targets. In the second system, the task is to pick industrial parts out of a bin. We show how the two tasks were decomposed and analyzed to yield the best match between perceptual capabilities and task requirements. Then, we introduce a general framework for task-based development of vision systems.
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