Abstract
The goal of the proposed hierarchical graphical models is to recognize various instances of different object classes in images, image sequences or other scene representations like e.g. occupancy grid maps. The term “object” in this context is used as a general term representing visual objects, visual parts, visual features, visual primitives, but also activities, actions or motion primitives. In the following we will regard two different kinds of hierarchies:A compositional hierarchy and a similarity hierarchy. In compositional hierarchies the structure of a parent node is defined by its children, where edges define the spatial or spatiotemporal relation between the parent and the children nodes. In this manner complex high-level nodes can be recursively defined based on simple low-level features. Similarity hierarchies, on the other hand, describe similarities among objects, and among parts. In this work, they will be combined with a coarse-to-fine search by means of scale space representation. They are used to increase the robustness of the representation as well as the overall runtime performance.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Spehr, J. (2015). Hierarchical Graphical Models. In: On Hierarchical Models for Visual Recognition and Learning of Objects, Scenes, and Activities. Studies in Systems, Decision and Control, vol 11. Springer, Cham. https://doi.org/10.1007/978-3-319-11325-8_3
Download citation
DOI: https://doi.org/10.1007/978-3-319-11325-8_3
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11324-1
Online ISBN: 978-3-319-11325-8
eBook Packages: EngineeringEngineering (R0)