Please use this identifier to cite or link to this item:
https://doi.org/10.1007/978-3-540-79547-6_18
DC Field | Value | |
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dc.title | Communication-aware face detection using noc architecture | |
dc.contributor.author | Lai H.-C. | |
dc.contributor.author | Marculescu R. | |
dc.contributor.author | Savvides M. | |
dc.contributor.author | Chen T. | |
dc.date.accessioned | 2018-08-21T05:05:54Z | |
dc.date.available | 2018-08-21T05:05:54Z | |
dc.date.issued | 2008 | |
dc.identifier.citation | Lai H.-C., Marculescu R., Savvides M., Chen T. (2008). Communication-aware face detection using noc architecture. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 5008 LNCS : 181-189. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-540-79547-6_18 | |
dc.identifier.isbn | 3540795464 | |
dc.identifier.isbn | 9783540795469 | |
dc.identifier.issn | 03029743 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/146245 | |
dc.description.abstract | Face detection is an essential first step towards many advanced computer vision, biometrics recognition and multimedia applications, such as face tracking, face recognition, and video surveillance. In this paper, we proposed an FPGA hardware design with NoC (Network-on-Chip) architecture based on an AdaBoost face detection algorithm. The AdaBoost-based method is the state-of-the-art face detection algorithm in terms of speed and detection rates and the NoC provides high communication capability architecture. This design is verified on a Xilinx Virtex-II Pro FPGA platform. Simulation results show the improvement in speed 40 frames per second compared to software implementation. The NoC architecture provides scalability so that our proposed face detection method can be sped up by adding multiple classifier modules. | |
dc.source | Scopus | |
dc.subject | Face detection | |
dc.subject | Hardware Architecture | |
dc.subject | Network-on-Chip | |
dc.type | Conference Paper | |
dc.contributor.department | OFFICE OF THE PROVOST | |
dc.contributor.department | DEPARTMENT OF COMPUTER SCIENCE | |
dc.description.doi | 10.1007/978-3-540-79547-6_18 | |
dc.description.sourcetitle | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | |
dc.description.volume | 5008 LNCS | |
dc.description.page | 181-189 | |
dc.published.state | published | |
Appears in Collections: | Staff Publications |
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