The Reproduction Angular Error for Performance Evaluation

Recently, Transactions on Pattern Analysis and Machine Intelligence accepted a paper titled “The Reproduction Angular Error for Evaluating the Performance of Illuminant Estimation Algorithms” by Graham Finlayson, Roshanak Zakizadeh and Arjan Gijsenij. In this paper, we make a case for using a different performance metric than the traditional recovery angular error. This new metric, termed reproduction angular error, is defined as the angle between the RGB of a white surface when the actual and estimated illuminations are ‘divided out’. Contrary to the traditional error metric, the new error ties algorithm performance to how the illuminant estimates are actually used in practice. In future work, we strongly recommend using the reproduction angular error when comparing algorithms.