|제목(국문)||CPU와 GPU의 병렬 처리를 이용한 고속 물체 인식 알고리즘 구현|
|제목(영문)||The Implementation of Fast Object Recognition Using Parallel Processing on CPU and GPU|
정용한 (Young-Han Jung ,인하대학교 ) ▷공저자네트워크등록하기
박은수 (Eun-Soo Park ,인하대학교 ) ▷공저자 네트워크 보기
최학남 (Xuenan Cui ,인하대학교 ) ▷공저자네트워크등록하기
김학일 (Hak-ll Kim ,인하대학교 ) ▷공저자네트워크등록하기
허욱렬 (Uk-Youl Huh ,인하대학교 ) ▷공저자네트워크등록하기
|초록||This paper presents a fast feature extraction method for autonomous mobile robots utilizing parallel processing and based
on OpenMP, SSE (Streaming SIMD Extension) and CUDA programming. In the first step on CPU version, the algorithms and codes
are optimized and then implemented by parallel processing. The parallel algorithms are debugged to maintain the same level of
performance and the process for extracting key points and obtaining dominant orientation with respect to key points is parallelized.
After extraction, a parallel descriptor via SSE instructions is constructed. And the GPU version also implemented by parallel
processing using CUDA based on the SIFT. The GPU-Parallel descriptor achieves an acceleration up to five times compared with the
CPU-Parallel descriptor, but it shows the lower performance than CPU version. CPU version also speed-up the four and half times
compared with the original SIFT while maintaining robust performance.
|keyword||parallel processing, OpenMP, SSE, CUDA, SIFT, SURF|