Scalable Multi-class Object Detection

8 years 2 months ago
Scalable Multi-class Object Detection
Scalability of object detectors with respect to the number of classes is a very important issue for applications where many object classes need to be detected. While combining single-class detectors yields a linear complexity for testing, multi-class detectors that localize all objects at once come often at the cost of a reduced detection accuracy. In this work, we present a scalable multi-class detection algorithm which scales sublinearly with the number of classes without compromising accuracy. To this end, a shared discriminative codebook of feature appearances is jointly trained for all classes and detection is also performed for all classes jointly. Based on the learned sharing distributions of features among classes, we build a taxonomy of object classes. The taxonomy is then exploited to further reduce the cost of multi-class object detection. Our method has linear training and sublinear detection complexity in the number of classes. We have evaluated our method on the challeng...
Nima Razavi, Juergen Gall, Luc VanGool
Added 05 Apr 2011
Updated 29 Apr 2011
Type Journal
Year 2011
Where CVPR
Authors Nima Razavi, Juergen Gall, Luc VanGool
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