In case you missed it at our open house last Thursday, check out this video of the real-time object detection system demonstrated by Daniel Goehring, a DAAD postdoc in our Audio and Multimedia Group. It's able to quickly detect household objects - and can even identify a can of Pringles! The video is below; here's the abstract:

Object detection and classification is an important field within computer vision. Subtasks include the derivation of the position of an object within the image and its classification. In this demo we show an object detection approach, applied for 30 different household objects. The approach is based on the Deformable Parts Model algorithm, which uses HOG features and linear SVM to find the different part locations of an object. We use sparselets and a Cuda-Implementation to run our algorithm with 3-7 Hz.