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Discriminative Feature Co-Occurrence Selection for Object Detection
July 2008 (vol. 30 no. 7)
pp. 1257-1269
ASCII Text
x 
 
Takeshi Mita, Toshimitsu Kaneko, Bjorn Stenger, Osamu Hori, "Discriminative Feature Co-Occurrence Selection for Object Detection," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30, no. 7, pp. 1257-1269, July, 2008.
 
 
BibTex
x
 
@article{ 10.1109/TPAMI.2007.70767,
author = {Takeshi Mita and Toshimitsu Kaneko and Bjorn Stenger and Osamu Hori},
title = {Discriminative Feature Co-Occurrence Selection for Object Detection},
journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume = {30},
number = {7},
issn = {0162-8828},
year = {2008},
pages = {1257-1269},
doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2007.70767},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Pattern Analysis and Machine Intelligence
TI - Discriminative Feature Co-Occurrence Selection for Object Detection
IS - 7
SN - 0162-8828
SP1257
EP1269
EPD - 1257-1269
A1 - Takeshi Mita,
A1 - Toshimitsu Kaneko,
A1 - Bjorn Stenger,
A1 - Osamu Hori,
PY - 2008
KW - Statistical
KW - Feature evaluation and selection
KW - Face and gesture recognition
KW - Machine learning
VL - 30
JA - IEEE Transactions on Pattern Analysis and Machine Intelligence
ER -
 
This paper describes an object detection framework that learns the discriminative co-occurrence of multiple features. Feature co-occurrences are automatically found by Sequential Forward Selection at each stage of the boosting process. The selected feature co-occurrences are capable of extracting structural similarities of target objects leading to better performance. The proposed method is a generalization of the framework proposed by Viola and Jones, where each weak classifier depends only on a single feature. Experimental results obtained using four object detectors, for finding faces and three different hand gestures, respectively, show that detectors trained with the proposed algorithm yield consistently higher detection rates than those based on their framework while using the same number of features.

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Index Terms:
Statistical, Feature evaluation and selection, Face and gesture recognition, Machine learning
Citation:
Takeshi Mita, Toshimitsu Kaneko, Bjorn Stenger, Osamu Hori, "Discriminative Feature Co-Occurrence Selection for Object Detection," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30, no. 7, pp. 1257-1269, July 2008, doi:10.1109/TPAMI.2007.70767
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