The goal MILAB Machine Perception research is to interpret and organize information coming from distributed multimodal sensors. Sensors can be dynamic or static imaging devices or other multimedia sources. Spatio-temporal information analysis enables us to recognize and classify events such as unusual motion or voice patterns, or time series concept drifts. We place special emphasis on machine learning, data mining, human perception, geometrical optics, mutimodal sensor fusion, optimization methods and variational analysis in areas such as image and video processing, biometrical identification, connections with sensor networks, Geographical Information Systems, and computer graphics.