상세정보
학술대회
Reliable Object Detection and Segmentation using Inpainting
- 저자
- 정지훈, 유상원, 최성록, 김성락
- 발행일
- 201210
- 출처
- International Conference on Intelligent Robots and Systems (IROS) 2012, pp.3871-3876
- 협약과제
- 12MC2200, 실외환경에 강인한 도로기반 저가형 자율주행 기술 개발, 유원필
- 초록
- This paper presents a novel object detection and segmentation method utilizing an inpainting algorithm. Inpainting is a concept of recovering missing image regions based on their surroundings, which were originally used for restoration of damaged paintings. In this paper, we newly utilize inpainting to judge whether an object candidate region includes the foreground object or not. The key idea is that if we erase a certain region from an image, the inpainting algorithm is expected to recover the erased image only when it belongs a background area (i.e. only when there is no object in it). By measuring the similarity between the inpainted region and the original image region, our approach filters out false detections while maintaining true object detections. Furthermore, we take advantage of the inpainting for object segmentation, since our approach is designed to explicitly distinguish foreground areas from its background. Experimental results confirm that our approach applied to baseline detectors enables better recognition of objects, obtaining higher accuracies. We illustrate how our inpainting-based detection/segmentation approach benefits the object detection using two different pedestrian datasets. © 2012 IEEE.
- KSP 제안 키워드
- False detection, Inpainting Algorithm, Object detection, Object segmentation, Recognition of objects, Regions based, Segmentation approach, segmentation method