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Tracking Multiple Moving Objects Based on the Kalman Filter
Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
2016 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Object tracking is an important subject in computer vision. The tracking process includes two steps. The first step is background subtraction to detect the moving objects. The second step is using the filters, such as the Kalman filter or particle filter to track the detected objects. In this thesis, the Kalman filter and particle filter algorithms are simulated using a simple test video. An algorithm for tracking multiple moving birds in sky using the Kalman filter is presented. The objective of tracking is to analyse video sequences which is obtained from a fixed camera monitoring and track the birds in every frame and predict the birds’ location in the next frame. 15 videos are tested using the Kalman filter in this thesis. Finally, the tracking system should be implemented in GPU.

Place, publisher, year, edition, pages
2016. , 41 p.
Keyword [en]
Kalman filter, Multiple objects tracking, GPU
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:miun:diva-28040Local ID: EL-V16-A2-009OAI: oai:DiVA.org:miun-28040DiVA: diva2:941132
Subject / course
Electronics EL1
Educational program
International Master's Programme in Electronics Design TELAA 120 higher education credits
Supervisors
Examiners
Available from: 2016-06-22 Created: 2016-06-22 Last updated: 2016-06-22Bibliographically approved

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Jia, Jingyi
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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • de-DE
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Output format
  • html
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