@inproceedings{1e240dbd8ae6450889a990a48d85cfd7,
title = "Object categorization based on a supervised mean shift algorithm",
abstract = "In this work, we present a C++ implementation of object categorization with the bag-of-word (BoW) framework. Unlike typical BoW models which consider the whole area of an image as the region of interest (ROI) for visual codebook generation, our implementation only considers the regions of target objects as ROIs and the unrelated backgrounds will be excluded for generating codebook. This is achieved by a supervised mean shift algorithm. Our work is on the benchmark SIVAL dataset and utilizes a Maximum Margin Supervised Topic Model for classification. The final performance of our work is quite encouraging.",
author = "Ruo Du and Qiang Wu and Xiangjian He and Jie Yang",
year = "2012",
doi = "10.1007/978-3-642-33885-4_64",
language = "English",
isbn = "9783642338847",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
number = "PART 3",
pages = "611--614",
booktitle = "Computer Vision, ECCV 2012 - Workshops and Demonstrations, Proceedings",
address = "Germany",
edition = "PART 3",
note = "Computer Vision, ECCV 2012 - Workshops and Demonstrations, Proceedings ; Conference date: 07-10-2012 Through 13-10-2012",
}