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Design of an Evaluation Platform for multimodal 3D Data

Sensor Fusion for 3D data is a popular topic. Multisensor data combination enhance the qualities of each other while single sensor lacks accuracy. In this thesis, an evaluation platform for Multimodal 3D data from Kinect v2 and Microphone Array is designed and implemented by using ReactJS. In automotive industry and computer vision area, 3D detection and localization are widely used. Solutions of 3D detection and localization using different measurement systems are discussed in a large number of papers. Data Fusion systems are normally using ultrasound based, radio waves based, Time-of-Flight, structured light, stereo cameras and sound based sensors. All of these measurement systems might provide different 3D data models. And each system works fine separately. However, in some cases, multiple measurement systems need to work together. Their 3D data sets are different and could not be compared and combined directly. In order to simplify the design process of multiple measurement systems, this web based evaluation platform is focused on comparison and combination of 3D data sets from different coordinate systems. It provides a quick and easy development method between multiple measurement systems. In this thesis, an evaluation platform which based on Kinect v2 body detection and microphone array sound detection systems will be discussed. First an introduction about project overview is given. The second section of this paper deals with several project related technologies. The third section provides the concept of this project. The forth section describes development and implement detail. The next section is about data visualization and statistical analysis. Further the final results, evaluation and discussion are given.

Identiferoai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:31587
Date11 September 2018
CreatorsXu, Chengjie
ContributorsHardt, Wolfram, Hardt, Wolfram, Technische Universität Chemnitz
Source SetsHochschulschriftenserver (HSSS) der SLUB Dresden
LanguageEnglish
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/acceptedVersion, doc-type:masterThesis, info:eu-repo/semantics/masterThesis, doc-type:Text
Rightsinfo:eu-repo/semantics/openAccess

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