Volume 18 | Issue 12

The scope of the Periodical is the various aspects of research in multimedia technology and applications of multimedia, including, but not limited to, circuits, networking, signal processing, systems, software, and systems integration, as represented by the Fields of Interest of the sponsors.

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Editor

Wenwu Zhu
Department of Computer Science
Tsinghua University
Beijing, China
wwzhu@tsinghua.edu.cn

Articles

Social images, which are images uploaded and shared on social networks, are used to express users’ emotions. Inferring emotional tags from social images is of great importance; it can benefit many applications, such as image retrieval and recommendation. Whereas previous related research has primarily focused on exploring image visual features, we aim to address this problem by... Read more on IEEE Xplore

Massive open online courses and other forms of remote education continue to increase in popularity and reach. The ability to efficiently proctor remote online examinations is an important limiting factor to the scalability of this next stage in education. Presently, human proctoring is the most common approach of evaluation, by either requiring the test taker to visit an examination center, or by... Read more on IEEE Xplore

Complex event detection has been progressively researched in recent years for the broad interest of video indexing and retrieval. To fulfill the purpose of event detection, one needs to train a classifier using both positive and negative examples. Current classifier training treats the negative videos as equally negative. However, we notice that many negative videos resemble the positive videos... Read more on IEEE Xplore

In this paper, we propose a pixel fusion-based stereo image retargeting method, which could adaptively retarget stereo images with flexible aspect ratios, simultaneously preserving the depth. Retargeting each image independently by the pixel fusion method ignores the disparity relationship between pixels in the image pair and hence will introduce the distortion of disparity. To address this issue... Read more on IEEE Xplore

Data fusion is used to integrate features from heterogenous data sources into a consistent and accurate representation for certain learning tasks. As an effective technique for data fusion, unsupervised multimodal feature representation aims to learn discriminative features, indicating the improvement of classification and clustering performance of learning algorithms. However, it is a... Read more on IEEE Xplore