Social-Sensed Multimedia Computing

M ultimedia computing, which ultimately aims to deliver multimedia content to users according to their information needs (intents), can be decomposed into various stages, such as multimedia compression (for storage), multimedia communication (for delivery), and multimedia content analysis (for intelligence). The first two stages are comparatively well studied, while multimedia analysis started becoming mainstream in the multimedia community at the end of the last century, with related technologies advancing quickly. However, understanding and predicting what multimedia content users need in different situations and contexts—the last-mile technology for delivering multimedia services—has not been well studied (see Figure 1). This negligence has resulted in a gap between multimedia data and the information needs of users, creating a bottleneck in advancing intelligent multimedia computing technologies for use in real-world applications. To bridge this gap, we need to invest more effort in understanding users, both individually and collectively. Fortunately, the explosive growth of social multimedia content on the Internet is revolutionizing the landscape of various multimedia applications. The new types of multimedia content, metadata, context information, and interaction behaviors in social multimedia present a significant opportunity to advance and augment multimedia and content-analysis techniques. Existing research in this area viewed social multimedia as a new research objective and thus proposed methods to exploit the new data types or solve the new problems. Here, we argue that the significance of social multimedia with respect to the field of multimedia goes far beyond the emergence of new types of data and problems.