Fibonacci heaps and their uses in improved network optimization algorithms
Journal of the ACM (JACM)
Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
Automatic Performance Evaluation for Video Text Detection
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Evaluating Multi-Object Tracking
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Performance evaluation of object detection and tracking in video
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part II
Detecting text in video frames
SPPR'07 Proceedings of the Fourth conference on IASTED International Conference: Signal Processing, Pattern Recognition, and Applications
Measures for the evaluation of segmentation methods used in model based people tracking methods
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Detecting text in video frames
SPPRA '07 Proceedings of the Fourth IASTED International Conference on Signal Processing, Pattern Recognition, and Applications
A two-stage scheme for text detection in video images
Image and Vision Computing
Evaluation framework for video OCR
ICVGIP'06 Proceedings of the 5th Indian conference on Computer Vision, Graphics and Image Processing
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Text detection and tracking is an important step in a video content analysis system as it brings important semantic clues which is a vital supplemental source of index information. While there has been a significant amount of research done on video text detection and tracking, there are very few works on performance evaluation of such systems. Evaluations of this nature have not been attempted because of the extensive effort required to establish a reliable ground truth even for a moderate video dataset. However, such ventures are gaining importance now. In this paper, we propose a generic method for evaluation of object detection and tracking systems in video domains where ground truth objects can be bounded by simple geometric shapes (polygons, ellipses). Two comprehensive measures, one each for detection and tracking, are proposed and substantiated to capture different aspects of the task in a single score. We choose text detection and tracking tasks to show the effectiveness of our evaluation framework. Results are presented from evaluations of existing algorithms using real world data and the metrics are shown to be effective in measuring the total accuracy of these detection and tracking algorithms.