In today's age, there is a lot of visual information that is generated in various fields, ranging from daily routine to specialized applications. Processing all these types of information efficiently is a valid concern and needs focused research. Most face detection algorithms have to deal with low quality data in videos, since they're mainly focused on surveillance applications, whose information capturing devices capture less information each frame. This paper reviews some state-of-the-art face detection algorithms and compares their processing efficiency on low and high quality videos. The comparative analysis reveals that these recent and modern algorithms do not work as effectively on high quality videos as they do on lower quality videos. This paper defines the need to focus research on analysis of high quality information in videos in an efficient manner, so as to keep up the pace of their analysis with the information that is generated.