Recursive Segmentation and Recognition Templates for 2D Parsing

Language and image understanding are two major goals of artificial intelligence which can both be conceptually formulated in terms of parsing the input signal into a hierarchical representation. Natural language researchers have made great progress by exploiting the 1D structure of language to design efficient polynomialtime parsing algorithms. By contrast, the two-dimensional nature of images makes it much harder to design efficient image parsers and the form of the hierarchical representations is also unclear. Attempts to adapt representations and algorithms from natural language have only been partially successful. In this paper, we propose a Hierarchical Image Model (HIM) for 2D image parsing which outputs image segmentation and object recognition. This HIM is represented by recursive segmentation and recognition templates in multiple layers and has advantages for representation, inference, and learning. Firstly, the HIM has a coarse-to-fine representation which is capable of capt...

• Type: Conference
• Year: 2008
• Where: NIPS
• Authors: Leo Zhu, Yuanhao Chen, Yuan Lin, Chenxi Lin, Alan L. Yuille
• Keywords: Hierarchical Representations, Image, Information Technology, Natural Language, NIPS 2008