Confidence rated boosting algorithm for generic object detection

In this paper we propose a confidence rated boosting algorithm based on Ada-boost for generic object detection. Confidence rated Ada-boost algorithm has not been applied to generic object detection problem; in that sense our work is novel. We represent images as bag of words, where the words are SIF...

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Main Authors: Zaidi, N.A., Suter, D.
Format: Conference Proceeding
Language:English
Subjects:
Boosting
Data mining
Face recognition
Frequency
Histograms
Machine learning
Object detection
Object recognition
Shape
Systems engineering and theory
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Suter, D.
description In this paper we propose a confidence rated boosting algorithm based on Ada-boost for generic object detection. Confidence rated Ada-boost algorithm has not been applied to generic object detection problem; in that sense our work is novel. We represent images as bag of words, where the words are SIFT descriptors extracted over some interest points. We compare our boosting algorithm to another version of boosting algorithm called Gentle-boost. Our approach generalizes well and performs equal or better than Gentle-boost. We show our results on four categories from the Caltech data sets, in terms of ROC curves.
doi_str_mv 10.1109/ICPR.2008.4761184
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source IEEE Electronic Library (IEL) Conference Proceedings
subjects Boosting
Data mining
Face recognition
Frequency
Histograms
Machine learning
Object detection
Object recognition
Shape
Systems engineering and theory
title Confidence rated boosting algorithm for generic object detection
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