Algorithm modification approach to improve the Kinect's performance in point cloud processing

Mingshao Zhang, Zhou Zhang, Sven K. Esche, Constantin Chassapis

Research output: Contribution to conferencePaperpeer-review

4 Scopus citations

Abstract

Since its introduction in 2010, Microsoft's Kinect input device for game consoles and computers has shown its great potential in a large number of applications, including game development, research and education. Many of these implementations are still in the prototype stages and exhibit a somewhat limited performance. These limitations are mainly caused by the quality of the point clouds generated by the Kinect, which include limited range, high dependency on surface properties, shadowing, low depth accuracy, etc. One of the Kinect's most significant limitations is the low accuracy and high error associated with its point cloud. The severity of these defects varies with the points' locations in the Kinect's camera coordinate system. The available traditional algorithms for processing point clouds are based on the same assumption that input point clouds are perfect and have the same characteristics throughout the entire point cloud. In the first part of this paper, the Kinect's point cloud properties (including resolution, depth accuracy, noise level and error) and their dependency on the point pixel location will be systematically studied. Second, the Kinect's calibration, both by hardware and software approaches, will be explored and methods for improving the quality of its output point clouds will be identified. Then, modified algorithms adapted to the Kinect's unique properties will be introduced. This method allows to better judge the output point cloud properties in a quantifiable manner and then to modify traditional computer vision algorithms by adjusting their assumptions regarding the input cloud properties to the actual parameters of the Kinect. Finally, the modified algorithms will be tested in a prototype application, which shows that the Kinect does have the potential for successful usage in educational applications if the according algorithms are design properly.

Original languageEnglish
DOIs
StatePublished - 2014
EventASME 2014 International Mechanical Engineering Congress and Exposition, IMECE 2014 - Montreal, Canada
Duration: 14 Nov 201420 Nov 2014

Conference

ConferenceASME 2014 International Mechanical Engineering Congress and Exposition, IMECE 2014
Country/TerritoryCanada
CityMontreal
Period14/11/1420/11/14

Keywords

  • Algorithms modification
  • Calibration
  • Kinect limitation
  • Microsoft Kinect

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