While current landmark detection algorithms offer a good approximation of the landmark locations, they are often unsuitable for the use in biological research. We present multimodal landmark detection approach, based on Point distribution model that detects a larger number of anthropologically relevant landmarks than the current landmark detection algorithms.
At the same time we show that improving detection accuracy of initial vertices, using image information, to which
the Point distribution model is fitted, increases both the overall accuracy and the stability of the detected landmarks.