A System for 3D Vehicle Tracking Using Multiple Cameras

Loading...
Thumbnail Image

Persistent link to this item

Statistics
View Statistics

Journal Title

Journal ISSN

Volume Title

Title

A System for 3D Vehicle Tracking Using Multiple Cameras

Alternative title

Published Date

2017-10

Publisher

Type

Thesis or Dissertation

Abstract

In this thesis, we present a 3D vehicle tracking system that allows 3D vehicle dimension estimation using fusion of information from multiple cameras. Compared to traditional 2D vehicle tracking systems with a single camera, the 3D tracking system can potentially improve tracking accuracy in the presence of similar noise, shadow or vehicle occlusion. Taking synchronized images from multiple cameras as inputs, the developed 3D vehicle tracking system first processes image frames using image processing techniques to derive vehicle silhouettes. Using a square roadside pattern derived from parallel traffic lanes, multiple cameras are calibrated using an extended vanishing points based approach and post-optimization by minimizing the projection error. After segmentation, objects in image frames are projected to the real world, in which the overlap of the same object would ideally correspond to the chassis of the object, and this allows estimation of vehicle length and width. Once vehicle length and width are obtained, they can be further used in each image frame to estimate the vehicle height. The base of the vehicle can be represented as an oriented rectangle. The height of the object is sought in the image view that would create the top of the hyper rectangle of the 3D vehicle that has the edge furthest away from the vehicle base rectangle. In the 3D vehicle tracking process, Kalman filter is used to predict the state of the vehicle in the real world to allow data association of the vehicles. Experiment results using realistic traffic videos of an intersection from two cameras have shown that the 3D vehicle tracking is fully functional. Vehicle dimension estimation results are mostly consistent in spite of some error caused by camera calibration and vehicle segmentation.

Keywords

Description

University of Minnesota M.S.E.C.E. thesis. October 2017. Major: Electrical Engineering. Advisor: Hua Tang. 1 computer file (PDF); 63 pages.

Related to

Replaces

License

Series/Report Number

Funding information

Isbn identifier

Doi identifier

Previously Published Citation

Other identifiers

Suggested citation

Subedi, Sukriti. (2017). A System for 3D Vehicle Tracking Using Multiple Cameras. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/218032.

Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.