Abstract
The lack of a substantial experimental side to computer vision has been pointed to at various times in the past as a serious problem that hinders advancement of the field. My own favorite example quote on this theme is the following:
... What is more interesting is that we are willing to develop one more edge detector, but we do not want to develop objective and quantitative methods to evaluate the performance of an edge detector. About three decades of research on edge detection has produced N edge detectors without a solid basis to evaluate the performance. In most disciplines, researchers evaluate the performance of a technique by a controlled set of experiments and specify the performance in clear objective terms. ...
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© 2000 Springer Science+Business Media Dordrecht
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Bowyer, K.W. (2000). Experiences with Empirical Evaluation of Computer Vision Algorithms. In: Klette, R., Stiehl, H.S., Viergever, M.A., Vincken, K.L. (eds) Performance Characterization in Computer Vision. Computational Imaging and Vision, vol 17. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-9538-4_1
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DOI: https://doi.org/10.1007/978-94-015-9538-4_1
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