International Symposium on Visual Computing

Advances in Visual Computing pp 115-126 | Cite as

Motion Priors Estimation for Robust Matching Initialization in Automotive Applications

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9474)


Tracking keypoints through a video sequence is a crucial first step in the processing chain of many visual SLAM approaches. This paper presents a robust initialization method to provide the initial match for a keypoint tracker, from the 1st frame where a keypoint is detected to the 2nd frame, that is: when no depth information is available. We deal explicitly with the case of long displacements. The starting position is obtained through an optimization that employs a distribution of motion priors based on pyramidal phase correlation, and epipolar geometry constraints. Experiments on the KITTI dataset demonstrate the significant impact of applying a motion prior to the matching. We provide detailed comparisons to the state-of-the-art methods.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Visual Sensorics and Information Processing Lab, C.S. DepartmentGoethe UniversityFrankfurtGermany
  2. 2.Computer Vision Laboratory, ISYLinköping UniversityLinköpingSweden

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