Research of hierarchical models includes following topics:

We deal with a problem of Multi-class Object Representation and present a framework for learning a hierarchical shape vocabulary capable of representing objects in hierarchical manner using a statistically important compositional shapes. The approach takes simple oriented contour fragments and learns their frequent spatial configurations. These are recursively combined into increasingly more complex and class specific shape compositions, each exerting a high degree of shape variability
As extension to LHOP model we have developed a shape descriptor capable of using compositional parts learnt using LHOP model to provide a descriptor that is compatible with HOG descriptor and can be easily used as direct replacement.
ViCoS Eye is an experimental online service that aims to demonstrate a state-of-the-art computer vision object detection and categorization algorithm developed in our laboratory. Web-service is available in a form of a web-page and in a form of an Android application.


Publications for the topic of Learning a Hierarchy of Parts