Best view selection of 3D models based on unsupervised feature learning and discrimination ability

The best view selection corresponds to the task of automatically selecting the most representative view of a 3D model. In this paper, we describe a benchmark for evaluation of best view selection algorithms. The benchmark consists of the preferred views ...

Compared with supervised learning for feature selection, it is much more difficult to select the discriminative features in unsupervised learning due to the lack of label information. Traditional unsupervised feature selection algorithms usually select ...

Feature selection is important and necessary especially for processing large scale data. Existing feature selection methods generally compute a discriminant value with respect to class variable for a feature to indicate its classification ability. Such ...