Accelerating gesture recognition algorithm using coarse grained reconfigurable architectures

Minsik Kim, Deokho Kim, Minyong Sung, Wonjae Lee, Jaehyun Kim, Won Woo Ro

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The gesture recognition algorithms have been widely used to realize the human-computer interaction in multimedia applications, but still have limitation of integration due to the computation overhead. For this reason, this paper proposes an acceleration method for the hand gesture recognition algorithm using CGRA. The proposed algorithm enables software pipelining and vectorization for the SRP architecture, which exploits both the instruction level parallelism and data level parallelism. Therefore, the proposed optimization method improves the utilization of the hardware resources in SRP and effectively accelerates the performance of the gesture recognition algorithm, achieving maximum speedup of 10.97.

Original languageEnglish
Title of host publicationICALIP 2014 - 2014 International Conference on Audio, Language and Image Processing, Proceedings
EditorsWanggen Wan, Fa-Long Luo, Xiaoqing Yu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages906-910
Number of pages5
ISBN (Electronic)9781479939022
DOIs
Publication statusPublished - 2015 Jan 13
Event4th International Conference on Audio, Language and Image Processing, ICALIP 2014 - Shanghai, China
Duration: 2014 Jul 72014 Jul 9

Publication series

NameICALIP 2014 - 2014 International Conference on Audio, Language and Image Processing, Proceedings

Other

Other4th International Conference on Audio, Language and Image Processing, ICALIP 2014
CountryChina
CityShanghai
Period14/7/714/7/9

Fingerprint

Reconfigurable architectures
Gesture recognition
Human computer interaction
Hardware

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design

Cite this

Kim, M., Kim, D., Sung, M., Lee, W., Kim, J., & Ro, W. W. (2015). Accelerating gesture recognition algorithm using coarse grained reconfigurable architectures. In W. Wan, F-L. Luo, & X. Yu (Eds.), ICALIP 2014 - 2014 International Conference on Audio, Language and Image Processing, Proceedings (pp. 906-910). [7009926] (ICALIP 2014 - 2014 International Conference on Audio, Language and Image Processing, Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICALIP.2014.7009926
Kim, Minsik ; Kim, Deokho ; Sung, Minyong ; Lee, Wonjae ; Kim, Jaehyun ; Ro, Won Woo. / Accelerating gesture recognition algorithm using coarse grained reconfigurable architectures. ICALIP 2014 - 2014 International Conference on Audio, Language and Image Processing, Proceedings. editor / Wanggen Wan ; Fa-Long Luo ; Xiaoqing Yu. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 906-910 (ICALIP 2014 - 2014 International Conference on Audio, Language and Image Processing, Proceedings).
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abstract = "The gesture recognition algorithms have been widely used to realize the human-computer interaction in multimedia applications, but still have limitation of integration due to the computation overhead. For this reason, this paper proposes an acceleration method for the hand gesture recognition algorithm using CGRA. The proposed algorithm enables software pipelining and vectorization for the SRP architecture, which exploits both the instruction level parallelism and data level parallelism. Therefore, the proposed optimization method improves the utilization of the hardware resources in SRP and effectively accelerates the performance of the gesture recognition algorithm, achieving maximum speedup of 10.97.",
author = "Minsik Kim and Deokho Kim and Minyong Sung and Wonjae Lee and Jaehyun Kim and Ro, {Won Woo}",
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Kim, M, Kim, D, Sung, M, Lee, W, Kim, J & Ro, WW 2015, Accelerating gesture recognition algorithm using coarse grained reconfigurable architectures. in W Wan, F-L Luo & X Yu (eds), ICALIP 2014 - 2014 International Conference on Audio, Language and Image Processing, Proceedings., 7009926, ICALIP 2014 - 2014 International Conference on Audio, Language and Image Processing, Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 906-910, 4th International Conference on Audio, Language and Image Processing, ICALIP 2014, Shanghai, China, 14/7/7. https://doi.org/10.1109/ICALIP.2014.7009926

Accelerating gesture recognition algorithm using coarse grained reconfigurable architectures. / Kim, Minsik; Kim, Deokho; Sung, Minyong; Lee, Wonjae; Kim, Jaehyun; Ro, Won Woo.

ICALIP 2014 - 2014 International Conference on Audio, Language and Image Processing, Proceedings. ed. / Wanggen Wan; Fa-Long Luo; Xiaoqing Yu. Institute of Electrical and Electronics Engineers Inc., 2015. p. 906-910 7009926 (ICALIP 2014 - 2014 International Conference on Audio, Language and Image Processing, Proceedings).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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T1 - Accelerating gesture recognition algorithm using coarse grained reconfigurable architectures

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N2 - The gesture recognition algorithms have been widely used to realize the human-computer interaction in multimedia applications, but still have limitation of integration due to the computation overhead. For this reason, this paper proposes an acceleration method for the hand gesture recognition algorithm using CGRA. The proposed algorithm enables software pipelining and vectorization for the SRP architecture, which exploits both the instruction level parallelism and data level parallelism. Therefore, the proposed optimization method improves the utilization of the hardware resources in SRP and effectively accelerates the performance of the gesture recognition algorithm, achieving maximum speedup of 10.97.

AB - The gesture recognition algorithms have been widely used to realize the human-computer interaction in multimedia applications, but still have limitation of integration due to the computation overhead. For this reason, this paper proposes an acceleration method for the hand gesture recognition algorithm using CGRA. The proposed algorithm enables software pipelining and vectorization for the SRP architecture, which exploits both the instruction level parallelism and data level parallelism. Therefore, the proposed optimization method improves the utilization of the hardware resources in SRP and effectively accelerates the performance of the gesture recognition algorithm, achieving maximum speedup of 10.97.

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Kim M, Kim D, Sung M, Lee W, Kim J, Ro WW. Accelerating gesture recognition algorithm using coarse grained reconfigurable architectures. In Wan W, Luo F-L, Yu X, editors, ICALIP 2014 - 2014 International Conference on Audio, Language and Image Processing, Proceedings. Institute of Electrical and Electronics Engineers Inc. 2015. p. 906-910. 7009926. (ICALIP 2014 - 2014 International Conference on Audio, Language and Image Processing, Proceedings). https://doi.org/10.1109/ICALIP.2014.7009926