Greedy refinement of object proposals via boundary‐aligned minimum bounding box search
Autor: | Kuk-Jin Yoon, Han-Mu Park, Dae Yong Cho |
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Rok vydání: | 2017 |
Předmět: |
Mathematical optimization
business.industry 02 engineering and technology 010501 environmental sciences Object (computer science) 01 natural sciences Object detection Minimum bounding box Bounding overwatch Sliding window protocol 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition Artificial intelligence Bounding interval hierarchy Greedy algorithm business Algorithm Software Greedy randomized adaptive search procedure 0105 earth and related environmental sciences Mathematics |
Zdroj: | IET Computer Vision. 12:357-363 |
ISSN: | 1751-9640 |
DOI: | 10.1049/iet-cvi.2017.0208 |
Popis: | Recently developed object detectors rely on automatically generated object proposals, instead of using a dense sliding window search scheme; generating good object proposals has therefore become crucial for improving the computational cost and accuracy of object detection performance. In particular, the shape and location errors of object proposals can be directly propagated to object detection unless some additional processes are adopted to refine the shape and location of bounding boxes. In this study, the authors demonstrate an object proposal refinement algorithm that improves the localisation accuracy and refines the shape of object proposals by searching a boundary-aligned minimum bounding box. They assume that an object consists of several image regions, and that the optimal object proposal is well aligned with image region boundaries. Based on this assumption, they design novel boundary-region alignment measures and then propose a greedy refinement method based on the proposed measures. Experiments on the PASCAL VOC 2007 dataset show that the proposed method produces highly well-localised object proposals and truly improves the quality of object proposals. |
Databáze: | OpenAIRE |
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