Tommy C. Poon

Scene change detection and feature extraction for MPEG-4 sequences

In this paper, we present a new, computationally efficient, effective technique for detection of abrupt scene changes in MPEG-4/2 compressed video sequences. We combine the dc image-based approach of Feng, Lo, and Mehrpour. The bit allocation-based approach has the advantage of computational simplicity, since it only requires entropy decoding of the sequence. Since extraction of dc images from I- Frames/Objects is simple, the dc image-based technique of Yeo is a good alternative for comparison of I- Frames/Objects. For P-Frames/Objects, however, Yeos algorithm requires additional computation. We find that the bit allocation-change based approach is prone to false detection in comparison to intracoded objects in MPEG-4 sequences. However, if a suspected scene/object change has been located accurately in a group of consecutive frames/objects, the bit allocation-based technique quickly and accurately locates the cut point therein. This motivates us to use dc image-based detection between successive I- Frames/Objects, to identify the subsequences with scene/object changes, and then use bit allocation-based detection to find the cut point therein. Our technique thus has only a marginally greater complexity than the completely bit allocation-based technique, but has greater accuracy. It is applicable to both MPEG-2 sequences and MPEG-4 multiple- object sequences. In the MPEG-4 multiple object case, we use a weighted sum of the change in each object of the frame, using the area of the object as the weight.

Fade-in/out scene change detection in the MPEG-1/2/4 compressed video domain

In this paper, we present a fade detection technique for indexing of MPEG-2 and MPEG-4 compressed video sequences. We declare a fade-in if the number of positive residual dc coefficients in P frames exceeds a certain percentage of the total number of non-zero dc coefficients consistently over several consecutive frames. Our fade-detection technique has fair accuracy and the advantage of high simplicity since it uses only entropy decoding and does not use computationally expensive inverse DCTs.