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The jacobs robotics approach to object recognition and localization in the context of the ICRA'11 Solutions in Perception Challenge

Narunas Vaškevičius, Kaustubh Pathak, Alexandru Eugen Ichim, Andreas Birk

Year
2012
Citations
24

Abstract

In this paper, we give an overview of the Jacobs Robotics entry to the ICRA'11 Solutions in Perception Challenge. We present our multi-pronged strategy for object recognition and localization based on the integrated geometric and visual information available from the Kinect sensor. Firstly, the range image is over-segmented using an edge-detection algorithm and regions of interest are extracted based on a simple shape-analysis per segment. Then, these selected regions of the scene are matched with known objects using visual features and their distribution in 3D space. Finally, generated hypotheses about the positions of the objects are tested by back-projecting learned 3D models to the scene using estimated transformations and sensor model. Our method won the second place among eight competing algorithms, only marginally losing to the winner.

Keywords

Artificial intelligenceComputer visionRoboticsObject (grammar)Cognitive neuroscience of visual object recognitionComputer scienceContext (archaeology)PerceptionEnhanced Data Rates for GSM EvolutionObject detection

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