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| Content Provider | PubMed Central |
|---|---|
| Author | Wang, Jinwei Ma, Xirong Zhu, Yuanping Sun, Jizhou |
| Copyright Year | 2014 |
| Abstract | 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. |
| Related Links | http://dx.doi.org/10.1155/2014/528080 |
| Starting Page | 528080 |
| File Format | |
| ISSN | 23566140 |
| e-ISSN | 1537744X |
| Journal | The Scientific World Journal |
| Volume Number | 2014 |
| Language | English |
| Publisher | Hindawi Publishing Corporation |
| Publisher Date | 2014-01-01 |
| Access Restriction | Open |
| Rights Holder | Hindawi Publishing Corporation |
| Subject Keyword | Biochemistry, Genetics and Molecular Biology(all) Environmental Science(all) Medicine(all) Research in Higher Education |
| Content Type | Text |
| Resource Type | Article |
| Subject | Medicine Biochemistry, Genetics and Molecular Biology Environmental Science |
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