Title of the tutorial

Graph-based Methods in Pattern Recognition and Document Image Analysis (GMPRDIA)


Many tasks in Pattern Recognition and Document Analysis are formulated as graph matching problems. Despite the NP-hard nature of the problem, fast and accurate approximations have led to significant progress in a wide range of applications in pattern recognition. Therefore learning graph-based representations and techniques is a real interest of the community. In this half day tutorial, we will present few methodologies for obtaining stable graph representation for different applications. Afterwards, we will explain different graph-based algorithms, methods and techniques and their evolution through ages for performing recognition, classification, detection in graph domain. Moreover, different applications of these algorithms in the field of Pattern Recognition and Document Analysis will also be described in the tutorial.


Structural Pattern Recognition, Graph-based representations, Graph matching, Graph embedding, Graph kernel, Graph serialization, Graph indexing, Graph hashing, Subgraph spotting