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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Goshorn, D. Junguk Cho Kastner, R. Mirzaei, S. |
| Copyright Year | 2010 |
| Abstract | The emergence of smart cameras has been fueled by increasingly advanced computing platforms that are capable of performing a variety of real-time computer vision algorithms. Smart cameras provide the ability to understand their environment. Object detection and behavior classification play an important role in making such observations. This paper presents a high-performance FPGA implementation of a generalized parts-based object detection and classifier that runs with capability of 266 frames/sec. The detection algorithm is easily reconfigured by simply loading a new representation into on-board memory, i.e., the FPGA can detect and classify a newly specified object and behavior without any changes to the hardware implementation. |
| Starting Page | 582 |
| Ending Page | 587 |
| File Size | 1716803 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424478422 |
| ISSN | 19461488 |
| e-ISBN | 9781424478439 |
| DOI | 10.1109/FPL.2010.114 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-08-31 |
| Publisher Place | Italy |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Pixel Field programmable gate arrays Object detection Indexes Correlation Buffer storage Random access memory real-time vision smart cameras FPGA object detection hardware acceleration |
| Content Type | Text |
| Resource Type | Article |
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