1. A method for detecting multi-object anomalies in transportation related video footage, said method comprising: receiving in an offline training phase a first input video sequence at a first traffic location and identifying at least one normal event involving P moving objects, where P is greater than 1; assigning in said offline training phase said at least one normal event in said first input video sequence to at least one normal event class and building a training dictionary suitable for joint sparse reconstruction; receiving in an online detection phase a second input video sequence captured at a second traffic location similar to said first traffic location and identifying at least one event involving P moving objects, and reconstructing in said online detection phase an approximation of said event within second input video sequence with respect to said training dictionary using a joint sparse reconstruction model.