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> 연구성과 > 국외저널
| 책임교수 | 원치선 |
|---|---|
| 논문명 | Nonuniform Video Size Reduction for Moving Objects |
| 논문종류 | SCI |
| 제1저자 | Anh Vu Le |
| 교신저자 | 원치선 |
| 공동저자 | 정승원 |
| Impact Factor | 1.219 |
| 개제학술지명 | SCIENTIFIC WORLD JOURNAL |
| Keyword | Video Resizing; |
| 게재일 | 2014 년 08 월 |
Moving objects of interest (MOOIs) in surveillance videos are detected and encapsulated by bounding boxes. Since moving objects are defined by temporal activities through the consecutive video frames, it is necessary to examine a group of frames (GoF) to detect the moving objects. To do that, the traces of moving objects in the GoF are quantified by forming a spatiotemporal gradient map (STGM) through the GoF. Each pixel value in the STGM corresponds to the maximum temporal gradient of the spatial gradients at the same pixel location for all frames in the GoF. Therefore, the STGM highlights boundaries of the MOOI in the GoF and the optimal bounding box encapsulating the MOOI can be determined as the local areas with the peak average STGM energy. Once an MOOI and its bounding box are identified, the inside and outside of it can be treated differently for object-aware size reduction. Our optimal encapsulation method for the MOOI in the surveillance videos makes it possible to recognize the moving objects even after the low bitrate video compressions.
*ITRC 기여율 = 1
*ITRC 기여율 = 1
