Stereo image de-fencing using smartphones

TL;DR

This paper introduces a novel stereo image de-fencing method that leverages disparity from stereo pairs captured by smartphones to accurately detect and remove fences, improving de-fencing quality over traditional video-based approaches.

Contribution

It presents a new approach using stereo disparity and an optimization framework with total variation prior for effective fence removal from images.

Findings

Successfully detects fence pixels using disparity information

Produces high-quality de-fenced images from stereo pairs

Outperforms traditional video-based de-fencing methods

Abstract

Conventional approaches to image de-fencing have limited themselves to using only image data in adjacent frames of the captured video of an approximately static scene. In this work, we present a method to harness disparity using a stereo pair of fenced images in order to detect fence pixels. Tourists and amateur photographers commonly carry smartphones/phablets which can be used to capture a short video sequence of the fenced scene. We model the formation of the occluded frames in the captured video. Furthermore, we propose an optimization framework to estimate the de-fenced image using the total variation prior to regularize the ill-posed problem.