Cheon Seog Kim

Measuring video quality on full scalability of H.264/AVC Scalable Video Coding

In heterogeneous network environments, it is mandatory to measure the grade of the video quality in order to guarantee the optimal quality of the video streaming service. Quality of Service (QoS) has become a key issue for service acceptability and user satisfaction. Although there have been many recent works regarding video quality, most of them have been limited to measuring quality within temporal and Signal-to-Noise Ratio (SNR) scalability. H.264/AVC Scalable Video Coding (SVC) has emerged and has been developed to support full scalability. This includes spatial, temporal, and SNR scalability, each of which shows different visual effects. The aim of this paper is to define and develop a novel video quality metric allowing full scalability. It focuses on the effect of frame rate, SNR, the change of spatial resolution, and motion characteristics using subjective quality assessment. Experimental results show the proposed quality metric has a high correlation to subjective quality and that it is useful in determining the video quality of SVC.

Quality Measurement Modeling on Scalable Video Applications

For various mobile applications, measuring the grade of the video quality is needed in order to guarantee the optimal quality of video streaming service. As H.264/AVC scalable video coding (SVC) has been emerged and developed to support full scalability including spatial, temporal, and signal-to-noise ratio (SNR) scalability, each of which shows different visual effect, it is necessary to measure video quality with full scalability. In this paper, we develop a novel video quality metric allowing full scalability through the subjective quality assessment. Experimental results show that the proposed quality metric has high correlation with subjective quality and is useful to determine the video quality of SVC.

MPEG-21-based scalable bitstream adaptation using medium grain scalability

H.264/AVC scalable video coding (SVC) aims at providing high video quality to users in heterogeneous multimedia usage environments. In order to create an adapted bitstream in an optimal way, an adaptation decision-taking algorithm is needed. This algorithm has to take into account the capabilities and the constraints of the targeted usage environment, as well as the properties of the scalable bitstream. In this paper, description tools part of MPEG-21 digital item adaptation (DIA) are used to characterize usage environments and scalable bitstreams, such as usage environment description (UED), universal constraints description (UCD), and adaptation quality of service (AdaptationQoS). Further, we also propose an adaptation decision-taking algorithm for the exploitation of medium grain scalability (MGS) in SVC. This algorithm was implemented in an adaptation decision-taking engine (ADTE). Our experimental results demonstrate the efficiency of the proposed adaptation decision-taking algorithm for the exploitation of MGS in SVC.

Semantic event detection in structured video using hybrid HMM/SVM

In this paper, we propose a new semantic event detection algorithm in structured video. A hybrid method that combines HMM with SVM to detect semantic events in video is proposed. The proposed detection method has some advantages that it is suitable to the temporal structure of event thanks to Hidden Markov Models (HMM) and guarantees high classification accuracy thanks to Support Vector Machines (SVM). The performance of the proposed method is compared with that of HMM based method, which shows the performance increase in both recall and precision of semantic event detection.

Quality metric for H.264/AVC scalable video coding with full scalability

Scalable Video Coding (SVC) is one of the promising techniques to ensure Quality of Service (QoS) in multimedia communication through heterogeneous networks. SVC compresses a raw video into multiple bitstreams composed of a base bitstream and enhancement bitstreams to support multi scalabilities such as SNR, temporal and spatial. Therefore, it is able to extract an appropriate bitstream from original coded bitstream without re-encoding to adapt a video to user environment. In this flexible environment, QoS has appeared as an important issue for service acceptability. Therefore, there has been a need for measuring a degree of video quality to guarantee the quality of video streaming service. Existing studies on the video quality metric have mainly focused on temporal and SNR scalability. In this paper, we propose an efficient quality metric, which allows for spatial scalability as well as temporal and SNR scalability. To this end, we study the effect of frame rate, SNR, spatial scalability and motion characteristics by using the subjective quality assessment, and then a new video quality metric supporting full scalability is proposed. Experimental results show that this quality metric has high correlation with subjective quality. Because the proposed metric is able to measure a degree of video quality according to the variation of scalability, it will play an important role at the extraction point for determining the quality of SVC.

Video contents summary using the combination of multiple MPEG-7 metadata

We propose a content-based summary generation method using MPEG-7 metadata. In this paper, the important events of video are defined and subsequently shot boundary detection is carried out. Then, we analyze the video contents in the shot with multiple content features using multiple MPEG-7 descriptors. In experiments with a golf-video, we combined motion activity, edge histogram and homogeneous texture for the detection of event. Further, the extracted segments and key-frames of each event are described by XML document. Experimental result shows that the proposed method gives reliable summary generation with robust event detection.

Development of subjective quality based adaptation system for SVC

In this paper, we present the development of adaptation system for SVC, where adaptation decision is based on subjective quality. To achieve video adaptation which is accordant to human visual perception, the subjective quality metric is adopted into the adaptation system. Since the subjective quality metric is modeled on the subjective perception of a video content, the proposed system can maximize the quality of service (QoS) for the given adapted content. To verify the usefulness of the proposed adaptation system, subjective quality assessments were performed. The experimental result showed the proposed adaptation system was useful for visual perception adaptation.

Perceptual quality measurement for scalable video at low spatial resolution in mobile environments

Environments for the delivery and consumption of multimedia are often very heterogeneous, due to the use of various terminals in varying network conditions. One example of such an environment is a wireless network providing connectivity to a plethora of mobile devices. H.264/AVC Scalable Video Coding (SVC) can be utilized to deal with diverse usage environments. However, in order to optimally tailor scalable video content along the temporal, spatial, or perceptual quality axes, a quality metric is needed that reliably models subjective quality. The major contribution of this paper is the development of a novel quality metric for scalable video bit streams having a low spatial resolution, targeting consumption in wireless video applications. The proposed quality metric allows modeling the temporal, spatial, and perceptual quality characteristics of SVC bit streams. This is realized by taking into account several properties of the compressed bit streams, such as the temporal and spatial variation of the video content, the frame rate, and PSNR values. An extensive number of subjective experiments have been conducted to construct and verify the reliability of our quality metric. The experimental results show that the proposed quality metric is able to efficiently reflect subjective quality. Moreover, the performance of the quality metric is uniformly high for video sequences with different temporal and spatial characteristics.

Digital item adaptation for color vision variations

As color is more widely used to carry visual information in the multimedia content, ability to perceive color plays a crucial role in getting visual information. Regardless of color vision variations, one should have visual information equally. This paper proposes the adaptation technique for color vision variations in the MPEG-21 Digital Item Adaptation (DIA). DIA is performed respectively for severe color vision deficiency (dichromats) and for mild color vision deficiency (anomalous trichromats), according to the description of user characteristics about color vision variations. Adapted images are tested by simulation program for color vision variations so as to recognize the appearance of the adapted images in the color deficient vision. Experimental result shows that proposed adaptation technique works well in the MPEG-21 framework.

Generation of MPEG-7 descriptor in compressed domain

We propose a technique for generating the MPEG-7 descriptor in compressed image/video data. Image processing in the transform domain is a much interesting area recently because compressed image and video data are becoming widely available with the data format like MPEG or JPEG.. In general, processing in the transform domain requires smaller data quantities, and lower computation complexity than that in the spatial domain. In this paper, we propose a generation algorithm of the MPEG-7 metadata in the compressed domain. We have developed an algorithm to get the homogeneous texture descriptor in the compressed domain.