Semantic analysis of image sequences using computer vision methods

Semantic analysis of image sequences using computer vision methods

by Eren Erdal Aksoy
Doctoral thesis
Date of Examination:2012-07-18
Date of issue:2012-10-11
Advisor:Prof. Dr. Florentin Wörgötter
Referee:Prof. Dr. Florentin Wörgötter
Referee:Prof. Dr. Wolfgang May
Persistent Address: http://dx.doi.org/10.53846/goediss-2571

 

 

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Abstract

English

Observing, learning, and imitating human skills are intriguing topics in cognitive robotics. The main problem in the imitation learning paradigm is the policy development. Policy can be defined as a mapping from an agent's current world state to actions. Thus, understanding and performing an observed human skill for a cognitive agent depends heavily upon the learned policy. So far, naive policies that use object and hand models with trajectory information have commonly been developed to encode and imitate various types of human manipulations. These approaches, on the one hand, can not be general enough since models are not learned by the agent itself but rather are provided by the designer in advance. It is also not sufficient to imitate complicated manipulations at the trajectory-level since even the same observed manipulation can have high variations in trajectories from demonstration to demonstration. Nevertheless, humans have the capability of recognizing and imitating observed manipulations without any problem. In humans, the chain of perception, learning, and imitation of manipulations is developed in conjunction with the interpretation of the manipulated objects. To compose a human-like perception-action chain the cognitive agent needs a generic policy that can extract manipulation primitives as well as the essential (invariant) relations between objects and manipulation actions. In this thesis, we introduce a novel concept, the so-called “Semantic Event Chain
Keywords: Semantic Event Chains; Scene Graphs; Object-Action Relations; Manipulation Actions
Schlagwörter: Semantic Event Chains; Scene Graphs; Relationen von Objekten und Handlungen
 
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