Robust identification of gradual shot-transition types

Many video related applications require identification of shot transitions and their type. Several algorithms for detecting both abrupt and gradual transitions exist. However, there is no integrated and robust framework for detecting transition types accurately. We show that combing the individual works of different researchers for identifying different transition types yields poor performance. An approach is presented using several algorithms working on patterns of effective average gradient, double chromatic difference, etc., such that the approach is robust to false detection or false-alarms. A comparison with standard approaches over 3 hours of experimental data on non-trivial video classes, such as commercials, MTV, sports, etc., shows the superiority of our approach.