Name
Abstract | ||
|---|---|---|
Corner extraction is an important task in many computer vision systems. The quality of the corners and the effi- ciency of the detection method are two very important as- pects that can greatly impact the accuracy, robustness and real-time performance of the corresponding corner-based vision system. In this paper we introduce a fast corner de- tector based on local binary-image regions. We verify the performance of the proposed method by measuring the re- peatability rate under various illumination, scale and mo- tion conditions. Our experimental results show that while the quality of the features are comparable with other con- ventional methods, ours delivers a faster performance. 1. MOTIVATION |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1109/ICARCV.2002.1234844 | ICARCV |
Keywords | Field | DocType |
vision system,binary image,edge detection,computer vision,feature extraction,real time | Structure from motion,Computer vision,Corner detection,Machine vision,Feature detection (computer vision),Interest point detection,Computer science,Edge detection,Scale space,Robustness (computer science),Artificial intelligence | Conference |
Citations | PageRank | References |
2 | 0.44 | 7 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Parvanesh Saeedi | 1 | 2 | 0.44 |
| D. G. Lowe | 2 | 15718 | 1413.60 |
| Peter Lawrence | 3 | 7 | 1.09 |