The paper addresses object localization via a distributed sensor network. A centralized estimation approach is undertaken along with a selective node activation strategy to ensure...
The handling of situations where multiple visual information occurs requires the fusion of visual information. This is a very common task found in the processing of multisource / ...
We present a new and efficient semi-supervised training method for parameter estimation and feature selection in conditional random fields (CRFs). In real-world applications suc...
In region surveillance applications, sensors oftentimes accumulate an overwhelmingly large amount of data, making it infeasible to process all of the collected data in real-time. ...
We advance new active object recognition algorithms that classify rigid objects and estimate their pose from intensity images. Our algorithms automatically detect if the class or p...