Formulation Of A N-Degree Polynomial For Depth Estimation using a Single Image

TL;DR

This paper proposes a monocular depth estimation method using an n-degree polynomial to map pixel depth to real depth, tailored for a specific camera through experimental calibration.

Contribution

It introduces a novel polynomial formulation for depth estimation from a single image, calibrated for individual cameras to improve accuracy.

Findings

Polynomial coefficients are unique for each camera setup.

The method effectively maps pixel depth to real-world depth.

Calibration with predefined lines enhances estimation accuracy.

Abstract

The depth of a visible surface of a scene is the distance between the surface and the sensor. Recovering depth information from two-dimensional images of a scene is an important task in computer vision that can assist numerous applications such as object recognition, scene interpretation, obstacle avoidance, inspection and assembly. Various passive depth computation techniques have been developed for computer vision applications. They can be classified into two groups. The first group operates using just one image. The second group requires more than one image which can be acquired using either multiple cameras or a camera whose parameters and positioning can be changed. This project is aimed to find the real depth of the object from the camera which had been used to click the photograph. An n-degree polynomial was formulated, which maps the pixel depth of an image to the real depth. In order to find the coefficients of the polynomial, an experiment was carried out for a particular lens and thus, these coefficients are a unique feature of a particular camera. The procedure explained in this report is a monocular approach for estimation of depth of a scene. The idea involves mapping the Pixel Depth of the object photographed in the image with the Real Depth of the object from the camera lens with an interpolation function. In order to find the parameters of the interpolation function, a set of lines with predefined distance from camera is used, and then the distance of each line from the bottom edge of the picture (as the origin line) is calculated.