Model-based object tracking in monocular image sequences of road traffic scenes
International Journal of Computer Vision
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
The Development and Comparison of Robust Methodsfor Estimating the Fundamental Matrix
International Journal of Computer Vision
Photorealistic Scene Reconstruction by Voxel Coloring
International Journal of Computer Vision
Robust Multiple Car Tracking with Occlusion Reasoning
Robust Multiple Car Tracking with Occlusion Reasoning
Object detection and matching in a mixed network of fixed and mobile cameras
AREA '08 Proceedings of the 1st ACM workshop on Analysis and retrieval of events/actions and workflows in video streams
A sparsity constrained inverse problem to locate people in a network of cameras
DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
Sparsity Driven People Localization with a Heterogeneous Network of Cameras
Journal of Mathematical Imaging and Vision
SCOOP: A Real-Time Sparsity Driven People Localization Algorithm
Journal of Mathematical Imaging and Vision
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We present a system for 3D reconstruction of traffic scenes. Traffic surveillance is a challenging scenario for 3D reconstruction in cases, where only a small number of views is available that do not contain much overlap. We address the possibilities and restrictions for modeling such scenarios with only a few cameras and introduce a compositor that allows rendering of the semi automatically generated 3D scenes. Some of the occurring problems concern camera images, which might show a common background area, but can still differ drastically in lighting effects. For foreground objects nearly no common visual information might be available, as angles between cameras may exceed even 90/spl deg/.