Evaluating and Improving the Depth Accuracy of Kinect for Windows v2

TL;DR

This paper assesses the depth accuracy of the Kinect v2 sensor, models its accuracy distribution, and introduces a trilateration method using multiple sensors to enhance depth measurement precision.

Contribution

It provides the first comprehensive accuracy evaluation of Kinect v2 and proposes a novel trilateration technique to improve depth accuracy with multiple devices.

Findings

Kinect v2's depth accuracy follows a cone distribution

Depth entropy effectively measures variance in depth data

Trilateration with multiple Kinects improves depth accuracy

Abstract

Microsoft Kinect sensor has been widely used in many applications since the launch of its first version. Recently, Microsoft released a new version of Kinect sensor with improved hardware. However, the accuracy assessment of the sensor remains to be answered. In this paper, we measure the depth accuracy of the newly released Kinect v2 depth sensor, and obtain a cone model to illustrate its accuracy distribution. We then evaluate the variance of the captured depth values by depth entropy. In addition, we propose a trilateration method to improve the depth accuracy with multiple Kinects simultaneously. The experimental results are provided to ascertain the proposed model and method.