| Budget Amount *help |
¥2,900,000 (Direct Cost: ¥2,900,000)
Fiscal Year 2006: ¥1,200,000 (Direct Cost: ¥1,200,000)
Fiscal Year 2005: ¥1,700,000 (Direct Cost: ¥1,700,000)
|
|---|
| Research Abstract |
The goal of this study is to provide high-quality Internet broadcasting using video content. For this purpose, I proposed a rate control method for streaming services with reference to video content, which control targets are spatial resolution, time resolution and frame size. In this study, I classified video programs into some groups in which large majority of users feel the same video quality, and analyzed factors (quality parameters) affecting subjective video quality. In addition, I applied the analysis results to an actual encoding system and demonstrated the implementation process of the proposed method on practical streaming servers. In this study, I obtained the following three results.
1. Video program classification for Internet broadcasting :
I conducted subjective assessments for 28 subjects using various types of 30 video programs, and proposed a method of classifying video programs into 6 groups. The classification method users feature description parameters which are the combination of semantic parameters (e.g. the importance of voice) and vision parameters (e.g. degree of motion intensity).
2. Designing a control algorithm of transmission rate :
I expressed the relationship between the subjective quality value of each group and the quality parameter values as an equation by multiple linear regression analysis, and designed a quality control algorithm using the equations. Efficient quality control can be achieved by selecting parameter values that maximize the subjective quality value under constraints.
3. Applying the method to an actual encoding system :
I used TMPGEnc (that is an MPEG-1 encoder) as an actual encoding system, and obtained the constraint for the proposed control algorithm. In this case, I adopted encoding bit-rate as the cost function (the constraint), and proposed a control method maximizing the subjective quality value under the constraint.
|
