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Proceedings Paper

Research environment for developing and testing object tracking algorithms
Author(s): Todd Schoepflin; Christopher Lau; Rohit Garg; Donglok Kim; Yongmin Kim
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Paper Abstract

We present an integrated research environment (RAVEN) that we have developed for the purpose of developing and testing object tracking algorithms. As a Windows application, RAVEN provides a user interface for loading and viewing video sequences and interacting with the segmentation and object tracking algorithms, which are included at run time as plug- ins. The plug-ins interact with RAVEN via a programming interface, enabling algorithm developers to concentrate on their ideas rather than on the user interface. Over the past two years. RAVEN has greatly enhanced the productivity of our researchers, enabling them to create a variety of new algorithms and extended RAVEN's capabilities via plug-ins. Examples include several object tracking algorithms, a live- wire segmentation algorithm, a methodology for the evaluation of segmentation quality, and even a mediaprocessor implementation of an object tracker. After implementing an algorithm, RAVEN makes it easy to present the results since it provides several mask display modes and output options for both image and video. We have found that RAVEN facilitates the entire research process, from prototyping an algorithm to visualization of the results to a mediaprocessor implementation.

Paper Details

Date Published: 29 December 2000
PDF: 9 pages
Proc. SPIE 4310, Visual Communications and Image Processing 2001, (29 December 2000); doi: 10.1117/12.411845
Show Author Affiliations
Todd Schoepflin, Univ. of Washington (United States)
Christopher Lau, Univ. of Washington (United States)
Rohit Garg, Univ. of Washington (United States)
Donglok Kim, Univ. of Washington (United States)
Yongmin Kim, Univ. of Washington (United States)


Published in SPIE Proceedings Vol. 4310:
Visual Communications and Image Processing 2001
Bernd Girod; Charles A. Bouman; Eckehard G. Steinbach, Editor(s)

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