Real time audio-visual object sequence collating at system test level

The ever-growing availability of multimedia data creates a strong requirement for efficient tools to manipulate and present data in an effective manner. The contributions of this paper consist of collation of audio and video parameters on system test level that allows for the analysis of test results. A key issue in automated summary construction is the evaluation of quality of audio and video with respect to the original content. Since there is no ideal solution a number of alternative approaches are available. Automatic audio and video summarization tools aim to validate the content without human intervention. Major task would be to collect different parameters from audio and video for effective comparison and quality analysis. The audio comparison is accomplished according to the relationship between feature parameters and the threshold value by algorithms. Automatic video comparison may assist based on the simulated user principal to evaluate the audio and video summary in a way which is automatic yet related to user's perceptions. To perform this task we consider several algorithms and compare their performance to define the most appropriate for our application. Here we don't describe what is important in a video and audio but rather what distinguished this video and audio from the original.