Advances in Engineering Advances in Engineering features breaking research judged by Advances in Engineering advisory team to be of key importance in the Engineering field. Papers are selected from over 10,000 published each week from most peer reviewed journals.
Pattern Recognition, Volume 48, Issue 3, March 2015, Pages 894-906.
Bharath Ramesh, Cheng Xiang, Tong Heng Lee.
Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117576.
Abstract
In this paper, we describe a classification framework for binary shapes that have scale, rotation and strong viewpoint variations. To this end, we develop several novel techniques. First, we employ the spectral magnitude of log-polar transform as a local feature in the bag-of-words model. Second, we incorporate contextual information in the bag-of-words model using a novel method to extract bi-grams from the spatial co-occurrence matrix. Third, a novel metric termed ‘weighted gain ratio’ is proposed to select a suitable codebook size in the bag-of-words model. The proposed metric is generic, and hence it can be used for any clustering quality evaluation task. Fourth, a joint learning framework is proposed to learn features in a data-driven manner, and thus avoid manual fine-tuning of the model parameters. We test our shape classification system on the animal shapes dataset and significantly outperform state-of-the-art methods in the literature.
