Sciweavers

Share
CVPR
2011
IEEE

Proposal Generation for Object Detection using Cascaded Ranking SVMs

8 years 1 months ago
Proposal Generation for Object Detection using Cascaded Ranking SVMs
Object recognition has made great strides recently. However, the best methods, such as those based on kernelSVMs are highly computationally intensive. The problem of how to accelerate the evaluation process without decreasing accuracy is thus of current interest. In this paper, we deal with this problem by using the idea of ranking. We propose a cascaded architecture which using the ranking SVM generates an ordered set of proposals for windows containing object instances. The top ranking windows may then be fed to a more complex detector. Our experiments demonstrate that our approach is robust, achieving higher overlap-recall values using fewer output proposals than the state-of-the-art. Our use of simple gradient features and linear convolution indicates that our method is also faster than the state-of-the-art.
Ziming Zhang, Jonathan Warrell, Philip Torr
Added 09 May 2011
Updated 09 May 2011
Type Journal
Year 2011
Where CVPR
Authors Ziming Zhang, Jonathan Warrell, Philip Torr
Comments (0)
books