3D Object Recognition

Min Sun is returning to University of Michigan at Ann Arbor, where he does computer vision research with particular interest in 3-D object recognition. During his summer here at Willow Garage, he focused on recognizing table-top objects like mice, mugs, and staplers in an office environment. Min is the the primary creator of rf_detector (Random Forest), which recognizes objects and their poses. The detector uses the stereo camera along with the texture light projector to collect images and the corresponding dense stereo point clouds. From there, rf_detector predicts the object type (i.e. mouse, mug, stapler) and its location and orientation. This information can be crucial to have before attempting object manipulation, as many object types, such as mugs, require careful handling.

In the future, Min will be looking for ways to scale up this approach to a wider range of object classes. Min continues to look for other features and model representations that make object recognition more robust.

Min also wrote the geometric_blur package, which calculates geometric blur descriptors.

Here are the slides from Min's final internship presentation describing his work on rf_detector and the detection pipeline.

Min Sun: 3D Object Detection on Scribd (Download PDF from ROS.org)