In this paper, a new selective sampling method for the active learning framework is presented. Initially, a small training set ? and a large unlabeled set ? are given. The goal is...
Labeling video data is an essential prerequisite for many vision applications that depend on training data, such as visual information retrieval, object recognition, and human act...
We present a generic framework for object segmentation using depth maps based on Random Forest and Graph-cuts theory, and apply it to the segmentation of human limbs in depth maps...
— In this paper we present a new approach for labeling 3D points with different geometric surface primitives using a novel feature descriptor – the Fast Point Feature Histogram...
Radu Bogdan Rusu, Andreas Holzbach, Nico Blodow, M...
A challenging problem of multi-label learning is that both the label space and the model complexity will grow rapidly with the increase in the number of labels, and thus makes the...