Coupled Object Detection and Tracking from Static Cameras and Moving Vehicles

Abstract-- We present a novel approach for multi-object tracking which considers object detection and spacetime trajectory estimation as a coupled optimization problem. Our approach is formulated in a Minimum Description Length hypothesis selection framework, which allows our system to recover from mismatches and temporarily lost tracks. Building upon a stateof-the-art object detector, it performs multi-view/multi-category object recognition to detect cars and pedestrians in the input images. The 2D object detections are checked for their consistency with (automatically estimated) scene geometry and are converted to 3D observations, which are accumulated in a world coordinate frame. A subsequent trajectory estimation module analyzes the resulting 3D observations to find physically plausible spacetime trajectories. Tracking is achieved by performing model selection after every frame. At each time instant, our approach searches for the globally optimal set of spacetime trajectories which...

• Type: Journal
• Year: 2008
• Where: PAMI
• Authors: Bastian Leibe, Konrad Schindler, Nico Cornelis, Luc J. Van Gool
• Keywords: PAMI 2008, Spacetime Trajectories, Spacetime Trajectory Estimation, Trajectory Estimation