Graduate Project

 

Detecting Anomalies in Object Appearance and Motion Dynamics Public Deposited

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https://ir.library.oregonstate.edu/concern/graduate_projects/6d5704477

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  • Machine common sense remains a broad, potentially unbounded problem in AI. Our focus is to move toward AI systems that can develop common-sense reasoning similar to humans to detect anomalies. In particular, we study the problem of detecting the violation of expectations when object appearance or motion dynamics change from simulated experiments. We have developed a system of multiple components to solve the problem of machine common sense. The system contains three main components: a two-stage tracker, a role assigner, and a rule-based reasoning agent. We evaluate our system on scenes from the DARPA Machine Common Sense, Passive Violation of Expectation task.
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