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학술지 The Computation Reduction in Object Detection via Composite Structure of Modified Integral Images
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저자
이대하, 김재홍, 김호희, 김순자
발행일
201701
출처
IEICE Transactions on Information and Systems, v.E100.D no.1, pp.229-233
ISSN
1745-1361
출판사
일본, 전자정보통신학회 (IEICE)
DOI
https://dx.doi.org/10.1587/transinf.2016EDL8158
협약과제
16PS1700, 인간 친화적 로봇 서비스 환경에서 판단 적합성 90%이상인 복합지식 기반 판단 및 의미기반 로봇 표현 기술 개발, 김재홍
초록
Object detection is the first step in the object recognition. According to the detection results, its following works are affected. However, object detection has a heavy resource requirement in terms of, computing power and memory. If an image is enlarged, the computational load required for object detection is also increased. An-integral-image-based method guarantees fast object detection. Once an integral image is generated, the speed of the object detection procedure remains fixed, regardless of the pattern region size. However, this becomes an even greater issue if the image is enlarged. In this paper, we propose the use of directional integral image based object detection. A directional integral image gives direction to an integral image, which can then be calculated from various directions. Furthermore, many unnecessary calculations, which typically occur when a partial integral image is used for object detection, can be avoided. Therefore, the amount of computation is reduced, compared with methods using integral images. In experiments comparing methods, the proposed method required 40% fewer computations.
KSP 제안 키워드
Computing power, Detection procedure, Image-based method, Integral Image, Object Recognition, Object detection, composite structure, computation reduction, computational load