Распознавание объекта в сцене на основе модели непроизвольного внимания с использованием OpenCL
| Parent link: | Технологии Microsoft в теории и практике программирования.— 2014.— [С. 97-99] |
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| Summary: | Заглавие с титульного листа. In this paper the algorithm of object tracking based on bottom-up attention is presented. First, the one-dimensional images were extracted from original image such as color and intensity maps. Then they combined into saliency map, which maximums corresponds to the most salient locations. Finally, the adaptive threshold is used to determine the location of objects on image. To accelerate the algorithm, the OpenCL version of the algorithm has been implemented. Experimental results demonstrate effectiveness of the algorithm for single and multiple object tracking. Implementation on OpenCL improves performance of the system. |
| Idioma: | ruso |
| Publicado: |
2014
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| Series: | Математическое моделирование и технологии высокопроизводительных вычислений |
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| Acceso en liña: | http://www.lib.tpu.ru/fulltext/c/2014/C28/037.pdf |
| Formato: | Electrónico Capítulo de libro |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=609520 |
| Summary: | Заглавие с титульного листа. In this paper the algorithm of object tracking based on bottom-up attention is presented. First, the one-dimensional images were extracted from original image such as color and intensity maps. Then they combined into saliency map, which maximums corresponds to the most salient locations. Finally, the adaptive threshold is used to determine the location of objects on image. To accelerate the algorithm, the OpenCL version of the algorithm has been implemented. Experimental results demonstrate effectiveness of the algorithm for single and multiple object tracking. Implementation on OpenCL improves performance of the system. |
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