Fast Reliable Multi-Scale Motion Region Detection in Video Processing

Motion region detection is an important vision topic usually tackled by a background subtraction principle, which has some practical restrictions. We hence propose a multi-scale motion region detection technique that can fast and reliably segment foreground motion regions from two successive video frames. The key idea is to leverage multi-scale structural aggregation to effectively accentuate real motion changes while suppressing trivial noisy changes. Consequently, this technique can be effectively applied to motion region-of-interest (ROI) based video coding. Our experiments show that the proposed algorithm can reliably extract motion regions and is less sensitive to thresholds than single-scale methods. Compared with a H.264/AVC encoder, the proposed semantic video encoder achieves a bitrate saving ratio of up to 34% at the similar video quality, besides an overall speedup factor of 2.6 to 3.6. The motion-ROI detection can process a 352 × 288 size video at 20 fps on an Intel Pentium 4 processor.