Efficient parallel implementation of active appearance model fitting algorithm on GPU.
The active appearance model (AAM) is one of the most powerful model-based object detecting and tracking methods which has been widely used in various situations. However, the high-dimensional texture representation causes very time-consuming computations, which makes the AAM difficult to apply to re...
| Publicado en: | Scientific World Journal pp. 528080 - 528081 |
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| Autores principales: | , , , |
| Formato: | research Journal Article |
| Publicado: |
Wiley-Blackwell
2014
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=103817834&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 103817834 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1537744X 1BX5 jtl: Scientific World Journal issn: 1537744X maglogo: N pubinfo: dt: 2014 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 103817834 103817834 NLM24723812 2012547787 10.1155/2014/528080 NLM24723812 PMC3958704 103817834 ppf: 528080 ppct: 1 formats: tig: atl: Efficient parallel implementation of active appearance model fitting algorithm on GPU. aug: au: Wang, Jinwei Ma, Xirong Zhu, Yuanping Sun, Jizhou affil: School of Computer Science and Technology, Tianjin University, Tianjin 300072, China ; College of Computer and Information Engineering, Tianjin Normal University, Tianjin 300387, China. sug: subj: Algorithms Models, Theoretical ab: The active appearance model (AAM) is one of the most powerful model-based object detecting and tracking methods which has been widely used in various situations. However, the high-dimensional texture representation causes very time-consuming computations, which makes the AAM difficult to apply to real-time systems. The emergence of modern graphics processing units (GPUs) that feature a many-core, fine-grained parallel architecture provides new and promising solutions to overcome the computational challenge. In this paper, we propose an efficient parallel implementation of the AAM fitting algorithm on GPUs. Our design idea is fine grain parallelism in which we distribute the texture data of the AAM, in pixels, to thousands of parallel GPU threads for processing, which makes the algorithm fit better into the GPU architecture. We implement our algorithm using the compute unified device architecture (CUDA) on the Nvidia's GTX 650 GPU, which has the latest Kepler architecture. To compare the performance of our algorithm with different data sizes, we built sixteen face AAM models of different dimensional textures. The experiment results show that our parallel AAM fitting algorithm can achieve real-time performance for videos even on very high-dimensional textures. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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