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.
Chen Chen, Jiangbo Lu, Do-Kyoung Kwon, Darnell Moore, Minh N. Do, "Accelerated Stereo Matching for Autonomous Vehicles using An Upright Pinhole Camera Model" in Proc. IS&T Int’l. Symp. on Electronic Imaging: Autonomous Vehicles and Machines, 2017, pp 18 - 21, https://doi.org/10.2352/ISSN.2470-1173.2017.19.AVM-013