Fast and Efficient Depth Map Estimation from Light Fields

Yuriy Anisimov, Didier Stricker

In: 3DVision 2017 |. International Conference on 3DVision (3DV-17) October 10-12 Qingdao China Conference Publishing Services (CPS) IEEE Xplore and CSDL 12/2017.


The paper presents an algorithm for depth map estimation from the light field images in relatively small amount of time, using only single thread on CPU. The proposed method improves existing principle of line fitting in 4- dimensional light field space. Line fitting is based on color values comparison using kernel density estimation. Our method utilizes result of Semi-Global Matching (SGM) with Census transform-based matching cost as a border initialization for line fitting. It provides a significant reduction of computations needed to find the best depth match. With the suggested evaluation metric we show that proposed method is applicable for efficient depth map estimation while preserving low computational time compared to others.


PID5040973_paper.pdf (pdf, 9 MB )

German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz