Paper
15 April 2010 Detection of moving objects from a moving platform in urban scenes
Author Affiliations +
Abstract
Moving object detection in urban scenes is important for the guidance of autonomous vehicles, robot navigation, and monitoring. In this paper moving objects are automatically detected using three sequential frames and tracked over a longer period. To this extend we modify the plane+parallax, fundamental matrix, and trifocal tensor algorithms to operate on three sequential frames automatically, and test their ability to detect moving objects in challenging urban scenes. Frame-to-frame correspondences are established with the use of SIFT keys. The keys that are consistently matched over three frames are used by the algorithms to distinguish between static objects and moving objects. The tracking of keys for the detected moving objects increases their reliability over time, which is quantified by our results. To evaluate the three different algorithms, we manually segment the moving objects in real world data and report the fraction of true positives versus false positives. Results show that the plane+parallax method performs very well on our datasets and we prove that our modification to this method outperforms the original method. The proposed combination of the advanced plane+parallax method with the trifocal tensor method improves on the moving object detection and their tracking for one of the four video sequences.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Frank B. ter Haar, Richard J. M. den Hollander, and Judith Dijk "Detection of moving objects from a moving platform in urban scenes", Proc. SPIE 7701, Visual Information Processing XIX, 770105 (15 April 2010); https://doi.org/10.1117/12.848034
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CITATIONS
Cited by 1 scholarly publication and 1 patent.
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KEYWORDS
Video

Cameras

Feature extraction

Motion models

Detection and tracking algorithms

Video surveillance

3D modeling

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