TY - GEN
T1 - More on weak feature
T2 - 5th Pacific-Rim Symposium on Video and Image Technology, PSIVT 2011
AU - Wang, Sheng
AU - Wu, Qiang
AU - He, Xiangjian
AU - Jia, Wenjing
PY - 2011
Y1 - 2011
N2 - In object detection research, there is a discussion on weak feature and strong feature, feature descriptors, regardless of being considered as 'weak feature descriptors' or 'strong feature descriptors' does not necessarily imply detector performance unless combined with relevant classification algorithms. Since 2001, main stream object detection research projects have been following the Viola Jone's weak feature (Haar-like feature) and AdaBoost classifier approach. Until 2005, when Dalal and Triggs have created the approach of a strong feature (Histogram of Oriented Gradient) and Support Vector Machine (SVM) framework for human detection. This paper proposes an approach to improve the salience of a weak feature descriptor by using intra-feature correlation. Although the intensity histogram distance feature known as Histogram Distance of Haar Regions (HDHR) itself is considered as a weak feature and can only be used to construct a weak learner to learn an AdaBoost classifier. In our paper, we explore the pairwise correlations between each and every histograms constructed and a strong feature can then be formulated. With the newly constructed strong feature based on histogram distances, a SVM classifier can be trained and later used for classification tasks. Promising experimental results have been obtained.
AB - In object detection research, there is a discussion on weak feature and strong feature, feature descriptors, regardless of being considered as 'weak feature descriptors' or 'strong feature descriptors' does not necessarily imply detector performance unless combined with relevant classification algorithms. Since 2001, main stream object detection research projects have been following the Viola Jone's weak feature (Haar-like feature) and AdaBoost classifier approach. Until 2005, when Dalal and Triggs have created the approach of a strong feature (Histogram of Oriented Gradient) and Support Vector Machine (SVM) framework for human detection. This paper proposes an approach to improve the salience of a weak feature descriptor by using intra-feature correlation. Although the intensity histogram distance feature known as Histogram Distance of Haar Regions (HDHR) itself is considered as a weak feature and can only be used to construct a weak learner to learn an AdaBoost classifier. In our paper, we explore the pairwise correlations between each and every histograms constructed and a strong feature can then be formulated. With the newly constructed strong feature based on histogram distances, a SVM classifier can be trained and later used for classification tasks. Promising experimental results have been obtained.
KW - Histogram distances
KW - Pairwise correlations
KW - SVM classifier
KW - Weak feature
UR - http://www.scopus.com/inward/record.url?scp=82155185355&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-25367-6_19
DO - 10.1007/978-3-642-25367-6_19
M3 - Conference contribution
AN - SCOPUS:82155185355
SN - 9783642253669
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 214
EP - 223
BT - Advances in Image and Video Technology - 5th Pacific Rim Symposium, PSIVT 2011, Proceedings
Y2 - 20 November 2011 through 23 November 2011
ER -