Automatic Locating of Anthropometric Landmarks on 3D Human Models

We present an algorithm for automatic locating of anthropometric landmarks on 3D human scans. Our method is based on learning landmark characteristics and the spatial relationships between them from a set of human scans where the landmarks are identified. The learned information is formulated by a pairwise Markov network. Each node of the network is a random variable corresponding to the position of a landmark. The edges of the network represent correlations between the positions of landmark pairs. Probabilistic inference is then performed over the Markov network to locate the landmarks. We evaluated the algorithm on 30 human models with different shapes. The results showed good accuracy for most of the landmarks.