This paper presents novel algorithms exploiting multiple camera inputs and segmentation techniques, which can be applied to image fusion, disparity detection and object extraction. Differently focused images, stereo pairs and both of them are used for fusion, disparity detection and object extraction, respectively. Firstly, image fusion is done by segmentation of each image and determination of focused regions per segment. An efficient decision criterion is developed taking a method of auto-focus into consideration. Secondly, disparity detection is executed by recursively applying segmentation and disparity detection per segment. A new clustering criterion is proposed in order to achieve good segmentation and high compression ratio of disparity maps simultaneously. Finally, object extraction is carried out by utilizing both the fusion result and the disparity map. Experiments are carried out, and they show us effectiveness of the proposed algorithms.
|出版ステータス||Published - 1996 12月 1|
|イベント||Proceedings of the 1996 IEEE International Conference on Image Processing, ICIP'96. Part 2 (of 3) - Lausanne, Switz|
継続期間: 1996 9月 16 → 1996 9月 19
|Other||Proceedings of the 1996 IEEE International Conference on Image Processing, ICIP'96. Part 2 (of 3)|
|Period||96/9/16 → 96/9/19|
ASJC Scopus subject areas
- コンピュータ ビジョンおよびパターン認識