|Appears in Collections:||Computing Science and Mathematics Conference Papers and Proceedings|
|Title:||Embedded Vision Systems: A Review of the Literature|
|Citation:||Bhowmik D & Appiah K (2018) Embedded Vision Systems: A Review of the Literature. In: Applied Reconfigurable Computing. Architectures, Tools, and Applications. Lecture Notes in Computer Science, 10824. International Symposium on Applied Reconfigurable Computing ARC 2018, Santorini, Greece, 02.05.2018-04.05.2018. Cham, Switzerland: Springer International Publishing, pp. 204-216. https://doi.org/10.1007/978-3-319-78890-6_17|
|Series/Report no.:||Lecture Notes in Computer Science, 10824|
|Conference Name:||International Symposium on Applied Reconfigurable Computing ARC 2018|
|Conference Dates:||2018-05-02 - 2018-05-04|
|Conference Location:||Santorini, Greece|
|Abstract:||Over the past two decades, the use of low power Field Programmable Gate Arrays (FPGA) for the acceleration of various vision systems mainly on embedded devices have become widespread. The reconfigurable and parallel nature of the FPGA opens up new opportunities to speed-up computationally intensive vision and neural algorithms on embedded and portable devices. This paper presents a comprehensive review of embedded vision algorithms and applications over the past decade. The review will discuss vision based systems and approaches, and how they have been implemented on embedded devices. Topics covered include image acquisition, preprocessing, object detection and tracking, recognition as well as high-level classification. This is followed by an outline of the advantages and disadvantages of the various embedded implementations. Finally, an overview of the challenges in the field and future research trends are presented. This review is expected to serve as a tutorial and reference source for embedded computer vision systems.|
|Status:||AM - Accepted Manuscript|
|Rights:||This is a post-peer-review, pre-copyedit version of a paper published in Voros N, Huebner M, Keramidas G, Goehringer D, Antonopoulos C & Diniz P (eds.) Applied Reconfigurable Computing. Architectures, Tools, and Applications. Lecture Notes in Computer Science, 10824. The final authenticated version is available online at: https://doi.org/10.1007/978-3-319-78890-6_17|
|Paper_73.pdf||Fulltext - Accepted Version||232.94 kB||Adobe PDF||View/Open|
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