Abstract | ||
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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. |
Year | DOI | Venue |
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2008 | 10.1109/ICPR.2008.4761184 | 19TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1-6 |
Keywords | Field | DocType |
roc curve,learning artificial intelligence,classification algorithms,feature extraction,visualization,bag of words,boosting | Bag-of-words model,Object detection,Scale-invariant feature transform,Data set,Pattern recognition,Visualization,Computer science,Feature extraction,Artificial intelligence,Boosting (machine learning),Statistical classification,Machine learning | Conference |
ISSN | Citations | PageRank |
1051-4651 | 1 | 0.37 |
References | Authors | |
11 | 2 |
Name | Order | Citations | PageRank |
---|---|---|---|
Nayyar Abbas Zaidi | 1 | 91 | 9.88 |
David Suter | 2 | 2247 | 126.18 |