원문정보
초록
영어
The boundaries of computer vision are especially challenged by partial occluded ob-ject recognition. In this paper, we proposed a new algorithm that used to recognize the partially occluded objects in 2-D images. Two different cases of occlusion are considered. Firstly, when an object missing some parts. Secondly, objects are overlapping each other. This approach uses contour of an object. Adaptive Window Positioning (AWP) uses to extract features from a contour. The proposed method uses the orientation field as fea-tures of the fragment. Dynamic Time Warping (DTW) works for matching and find the similarity between sub-images. As experiment result, the proposed recognition algorithm works without prior segmentation and robust to identify missing and overlapping objects and it can woks with strength occlusion.
목차
1. Introduction
2. Proposed Algorithm for Occluded Object
2.1. Dataset
2.2. Contour Detection
2.3. Features Extraction Using Adaptive Windowing Positioning (AWP)
2.4. Compute Orientation in Window
2.5. Matching Windows Using Dynamic Time Warping (DTW)
3. Experimental Result
4. Conclusion
Acknowledgments
References