Discriminative learning of Markov random fields for segmentation of 3D scan data

• Published in: 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) Vol. 2; pp. 169 - 176 vol. 2
• Main Authors: Anguelov, D., Taskarf, B., Chatalbashev, V., Koller, D., Gupta, D., Heitz, G., Ng, A.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 2005
• Subjects: Computer science; Image segmentation; Indoor environments; Large-scale systems; Layout; Markov random fields; Mobile robots; Robot localization; Robot sensing systems; Testing

We address the problem of segmenting 3D scan data into objects or object classes. Our segmentation framework is based on a subclass of Markov random fields (MRFs) which support efficient graph-cut inference. The MRF models incorporate a large set of diverse features and enforce the preference that a...