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Christensen H.I., Phillips P.J. (eds.) Empirical Evaluation Methods in Computer Vision

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Christensen H.I., Phillips P.J. (eds.) Empirical Evaluation Methods in Computer Vision
Издательство World Scientific, 2002, — 170 p.
For Computer Vision to mature from both scientific and industrial points of view, it is necessary to have methods and techniques for objective evaluation of computer vision algorithms. Towards this end, four workshops have been organised on this topic. The first workshop was on Performance Charactarisation in Computer Vision and organised in association with ECCV-96 in Cambridge, U.K. The second was the First Workshop on Empirical Evaluation Methods in Computer Vision held in conjunction with CVPR 98 in Santa Barbara, California. The third workshop was on Performance Characterisation and organised in association with ICVS-99 in the Canary Islands. The fourth was the Second Workshop on Empirical Evaluation Methods in Computer Vision held on 1 July 2000 in conjunction with ECCV 2000 in Dublin Ireland.
The primary goal of these workshops was to give researchers in the computer vision community a venue for presenting papers and discussing methods in evaluation. The secondary goals were to discuss strategies for gaining acceptance of evaluation methods and techniques in the computer vision community and to discuss approaches for facilitating long-term progress in evaluation.
This volume contains revised papers from the Second Workshop on Empirical Evaluation Methods in Computer Vision and a two additional papers considered essential to characterising state of the art of empirical evaluation in 2001. We were honoured that Prof. Bowyer and Prof. Forstner accepted our offer to give invited presentations. This volume includes a paper by Prof. Bowyer that summarises his presentation at the workshop.
Automated Performance Evaluation of Range Image Segmentation Algorithms
Training/Test Data Partitioning for Empirical Performance Evaluation
Analyzing PCA-based Face Recognition Algorithms: Eigenvector Selection and Distance Measures
Design of a Visual System for Detecting Natural Events by the Use of an Independent Visual Estimate: A Human Fall Detector
Task-Based Evaluation of Image Filtering within a Class of Geometry-Driven-Diffusion Algorithms
A Comparative Analysis of Cross-Correlation Matching Algorithms Using a Pyramidal Resolution Approach
Performance Evaluation of Medical Image Processing Algorithms
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