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BMVC
2010

A general boosting-based framework for active object recognition

9 years 3 months ago
A general boosting-based framework for active object recognition
We propose a novel general framework with a boosting algorithm to achieve active object classification by view selection. The proposed framework actively decides the next best view for the recognition task. It evaluates different information sources for top hypotheses, generates a voting matrix for candidate views and the view selection is achieved by picking up the one with the maximum votes. Three different sources similarity based on Implicit Shape Model, prior for model, and prior for views - are presented in the paper. Moreover, we convert view selection itself into a classification problem, and propose a boosting algorithm that is able to combine the previous sources. Experiments show that our algorithm produces a better strategy compared to the other baseline methods.
Zhaoyin Jia, Yao-Jen Chang, Tsuhan Chen
Added 10 Feb 2011
Updated 10 Feb 2011
Type Journal
Year 2010
Where BMVC
Authors Zhaoyin Jia, Yao-Jen Chang, Tsuhan Chen
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