Accelerated stereo matching for autonomous vehicles using an upright pinhole camera model

Chen Chen, Jiangbo Lu, Do Kyoung Kwon, Darnell Moore, Minh N. Do

Research output: Contribution to journalConference articlepeer-review


In this paper, we propose a new method for accelerating stereo matching in autonomous vehicles using an upright pinhole camera model. It is motivated by that stereo videos are more restricted when the camera is fixed on the vehicles driving on the road. Assuming that the imaging plane is perpendicular to the road and the road is generally flat, we can derive the current disparity based on the previous one and the flow. The prediction is very efficient that only requires two multiplications per pixel. In practice, this model may not hold strictly but we still can use it for disparity initialization. Results on real datasets demonstrate the our method reduces the disparity search range from 128 to 61 with only slightly accuracy decreasing.

Original languageEnglish (US)
Pages (from-to)18-21
Number of pages4
JournalIS and T International Symposium on Electronic Imaging Science and Technology
StatePublished - 2017
EventAutonomous Vehicles and Machines 2017, AVM 2017 - Burlingame, United States
Duration: Jan 29 2017Feb 2 2017

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Human-Computer Interaction
  • Software
  • Electrical and Electronic Engineering
  • Atomic and Molecular Physics, and Optics


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