Anyonewho has experienced artifacts or freezing play while watching a film or a live sporting event on TV is familiar with the frustration accompanying sudden quality degradation at a key moment. Notwithstanding, video services with blurred images may have far more severe consequences for video surveillance practitioners. Therefore, the Quality of Experience (QoE) concept for video content used for entertainment differs considerably from the quality of video used for recognition tasks. This is because in the latter case subjective user satisfaction depends only or almost only on the possibility of achieving a given functionality (event detection, object recognition). Additionally, the quality of video used by a human observer for recognitions tasks is considerably different from objective video quality used in computer processing (Computer Vision).