We present two approaches to extract regions from structured edge detection. While the state-of-the-art algorithm based on globalized probability of boundary (gPb) generates a hierarchical region tree, it entails significant computational load. In this work, we exploit an efficient algorithm for structured edge prediction to extract regions. To generate high quality regions, we develop a novel algorithm to link the structured edge and gPb hierarchical image segmentation framework with steerable filters. The extracted regions are grouped by the proposed hierarchical grouping method to generate object proposals for effective detection and recognition problems. We demonstrate the effectiveness of our region generation for image segmentation on the BSDS500 database, and region generation for object proposals on the PASCAL VOC 2007 benchmark database. Experimental results show that the proposed algorithm achieves the comparable or superior quality to the state-of-the-art methods.
|Title of host publication||Proceedings - 2015 IEEE Winter Conference on Applications of Computer Vision, WACV 2015|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||8|
|Publication status||Published - 2015 Feb 19|
|Event||2015 15th IEEE Winter Conference on Applications of Computer Vision, WACV 2015 - Waikoloa, United States|
Duration: 2015 Jan 5 → 2015 Jan 9
|Name||Proceedings - 2015 IEEE Winter Conference on Applications of Computer Vision, WACV 2015|
|Conference||2015 15th IEEE Winter Conference on Applications of Computer Vision, WACV 2015|
|Period||15/1/5 → 15/1/9|
Bibliographical notePublisher Copyright:
© 2015 IEEE.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Computer Vision and Pattern Recognition