Lab Meeting June 15th (David): Sparse Scene Flow Segmentation for Moving Object Detection (Intelligent Vehicles Symposium 2011)

Title: Sparse Scene Flow Segmentation for Moving Object Detection (Intelligent Vehicles Symposium 2011)

Authors: P. Lenz, J. Ziegler, A. Geiger, M. Roser

Abstract:
Modern driver assistance systems such as collision avoidance or intersection assistance need reliable information on the current environment. Extracting such information from camera-based systems is a complex and challenging task for inner city taffic scenarios. This paper presents an approach for object detection utilizing sparse scene flow. For consecutive stereo images taken from a moving vehicle, corresponding interest points are extracted. Thus, for every interest point, disparity and optical flow values are known and consequently, scene flow can be calculated. Adjacent interest points describing a similar scene flow are considered to belong to one rigid object. The proposed method does not rely on object classes and allows for a robust detection of dynamic objects in traffic scenes. Leading vehicles are continuously detected for several frames. Oncoming objects are detected within five frames after their appearance.

Link: http://www.rainsoft.de/publications/iv11b.pdf