The process of transcoding videos apart from being computationally intensive, can also be a rather complex procedure. The complexity refers to the choice of appropriate parameters for the transcoding engine, with the aim of decreasing video sizes, transcoding times and network bandwidth without degrading video quality beyond some threshold that event detectors lose their accuracy. This paper explains the need for transcoding, and then studies different video quality metrics. Commonly used algorithms for motion and person detection are briefly described, with emphasis in investigating the optimum transcoding configuration parameters. The analysis of the experimental results reveals that the existing video quality metrics are not suitable for automated systems, and that the detection of persons is affected by the reduction of bit rate and resolution, while motion detection is more sensitive to frame rate.