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)

Abstract

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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