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Title

Guest editorial: Special issue on computational image sensors and smart camera hardware

AuthorsFernández-Berni, J. ; Carmona-Galán, R. ; Sicard, Gilles; Dupret, Antoine
Issue Date3-Sep-2018
PublisherJohn Wiley & Sons
CitationInternational Journal of Circuit Theory and Applications 46(9): 1577-1579 (2018)
AbstractRecent advances in both software and hardware technologies are enabling the emergence of vision as a key sensorial modality in various application scenarios. Concerning hardware, all of the components along the signal chain play a significant role when it comes to implementing smart vision‐enabled systems. At the front end, new circuit structures for sensing, processing, and signal conditioning are adding functionalities in CMOS imagers beyond the mere generation of 2‐D intensity maps. Moreover, the development of vertical integration technologies is facilitating monolithic realizations of visual sensors where the incorporation of computational capabilities has no impact at all on image quality. Typically, the outcome of the front‐end device in a smart camera will be a preprocessed flow of information ready for further efficient analysis. At this point, specific ICs known as vision processing units can be inserted to accelerate the processing flow according to the targeted application. On the other hand, reconfigurability is a valuable asset in the ever‐changing field of vision. FPGAs leverage cutting‐edge digital technologies to offer flexible hardware for exploration of different memory arrangements, data flows, and processing parallelization. It is precisely parallelization for which GPUs constitute an interesting alternative in smart cameras when massive pixel‐level operation is required. This is the case of state‐of‐the‐art vision algorithms based on convolutional neural networks. At higher level, DSPs and multicore CPUs make software development notably easier at the cost of losing hardware specificity. Overall, this special issue aims at covering some of the latest research works in the vast ecosystem of hardware for artificial vision. All the accepted articles, briefly introduced below, have been reviewed by at least two experts in the field.
Publisher version (URL)https://doi.org/10.1002/cta.2551
URIhttp://hdl.handle.net/10261/195683
DOI10.1002/cta.2551
ISSN0098-9886
E-ISSN1097-007X
Appears in Collections:(IMSE-CNM) Artículos
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