Face spoofing detection ensemble via multistage optimisation and pruning

•We develop a solution for the face spoofing detection problem by fusing multiple anomaly experts using Weighted Averaging(WA).•We propose a novel three-stage optimisation approach to improve the generalisation capability and accuracy of the WA fusion.•We define a new score normalisation approach to support multiple anomaly detectors fusion.•We define an effective criterion to prune the WA to achieve better classification result and generalisation performance.•We experimentally demonstrate that the proposed anomaly-based WA achieves superior performance over state-of-theart methods.