Haar AIBO Detector

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Our system finds and tracks AIBOs in real time using an adaption of a face-detection algorithm that uses features based on Haar Waveletes.

Read the paper

JAMES E. YOUNG, Ehud Sharlin, and Jeffrey E. Boyd. Implementing Bubblegrams: The Use of Haar-like Features for Human-Robot Interaction. In Proceedings of the IEEE Conference on Automation Science and Engineering, 2006. IEEE CASE ’06, Shanghai, China, October 8-10, 2006, pages 308--313, IEEE Computer Society Press.

Detector Cases

This technique is a feature-based approach to detection that uses machine learning to select the best features. These features encapsulate intensity-distribution domain data about a region. This kind of data is very flexible to minor changes in images, so it is well suited to the detection of robots which often vibrate, move, and change shape. To give a complete cover, we split the detector into 5 simultaneous cases, shown in the image, and then combine the results with a voting technique to select the final match.

Difficult Case

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