Graph cuts optimization for multi-limb human segmentation in depth maps

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. First, from a set of random depth features, Random Forest is used to infer a set of label probabilities for each data sample. This vector of probabilities is used as unary term in

• Type: Journal
• Year: 2012
• Where: CVPR
• Authors: Antonio Hernández-Vela, Nadezhda Zlateva, Alexander Marinov, Miguel Reyes, Petia Radeva, Dimo Dimov, Sergio Escalera
• Keywords: Computer Vision, Cvpr 2012, Depth Maps, Human Limbs, Object Segmentation