In video compression algorithms, the quantization parameter (QP) is usually selected based on the relative complexity of the region in the picture as well as the overall bit usage. However, complexity-based rate-control algorithms do not take into account the fact that more complex objects, such as human faces, are more sensitive to degradation during perceptual video compression. To improve the overall perceived quality of the image, it is important to classify human faces as regions of interest (ROI) and preserve as much detail in those regions as possible. The challenge is developing a reliable algorithm that will operate in real time. This white paper details a low-complexity solution that is able to run on a single-core digital signal processor (DSP) as part of an encoder implementation.
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