Research paper written by To find the probability that the pose is likely to be in the foreground, the results of four functions are summed together. Each term is made up of its own function and serves a unique purpose as shown in the formula shown above. The function creates a probability score for each superpixel based off previous knowledge of from an Appearance model, it estimates the likelihood that a superpixel is part of the foreground. Bayes Theorem Steps for localizing and predicting actions Bayes Theorem creates a confidence score for each pixel within each frame. This score indicates the likelihood that a pixel is part of the foreground. Once every pixel is assigned a score, a heat map is generated that shows the location of the subject with darker colors with blue colors as non-important locations of that particular frame. Action Prediction using Support Vector Machines (SVMs) Research paper written by Center for Research in Computer Vision UCF Khurram Soomro, Haroon Idrees, Mubarak Shah