Automatic shot boundary detection has been an active research area for nearly a decade and has led to high performance detection algorithms for hard cuts, fades and wipes. Reliable dissolve detection, however, is still an unsolved problem. We present the first robust and reliable dissolve detection system. A detection rate of 75% was achieved while reducing the false alarm rate to an acceptable level of 16% on a test video set for which so far the best reported detection and false alarm rate had been 66% and 59%, respectively. In addition, a dissolve's temporal extent is estimated, too. The core ideas of our novel approach are firstly the creation of a dissolve synthesizer capable of creating in principle an infinite number of dissolve examples of any duration from a video database of raw video footage allowing us to use an advanced machine learning algorithm such as neural networks and support vector machines which require large training sets, secondly, two simple features capturing the characteristics of dissolves, thirdly, a fully temporal multi-resolution search based on a fixed position and fixed-scale transition/special effect detector enabling us to determine also the true duration of detected dissolves, and finally, a post processing step which uses global motion estimation to further reduce the number of falsely detected dissolves.