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Compared to other types of video programs, home video has some particularities according to the persons in shoot and objects to be screened (Lienhart et al., 1997). The study on home video analysis may benefit from its unique characteristics.
In general, a typical home video has certain structure characteristics: it contains a set of scenes, each composed of ordered and temporally adjacent shots that can be organized in clusters conveying semantic meaning. The fact is that home video recording imposes temporal continuity. Unlike other video programs, home video just records the life but not composes story, so every shot (clip of video captured in one place without interruption) may have the equal importance. In addition, filming home video with a temporal back-and-forth structure is rare. For example, on a vacation trip, people do not usually visit the same site twice. In other words, the content tends to be localized in time. Consequently, discovering the scene structure above shot level plays a key role in home video analysis. Video content organization based on shot clustering provides an efficient way of semantic video accessing and fast video editing.
Key Terms in this Chapter
Image Engineering (IE): An integrated discipline/subject comprising the study of all the different branches of image and video techniques. As a general term for all image techniques, it could be considered as a broad subject encompassing mathematics, physics, biology, physiology, psychology, electrical engineering, computer science, automation, etc. Its advances are also closely related to the development of telecommunications, biomedical engineering, remote sensing, document processing, industrial applications, etc.
Pan: One type of camera moving forms in capturing the scene image. It consists of the movement of camera around the vertical axis in the imaging plan.
Scene: In video analysis, it is composed of a series of consecutive shots that are coherent from the narrative point of view.
MPEG-7: An international standard named “Multimedia content description interface” (ISO/IEC 15938). It provides a set of audiovisual description tools, descriptors and description schemes for effective and efficient access (search, filtering and browsing) to multimedia content.
Object Segmentation: A process of image analysis. Its purpose is to extract the interesting region from image (corresponding to the interesting objects in scene).
Content-Based Image Retrieval (CBIR): A process framework for efficiently retrieving images from a collection by similarity. The retrieval relies on extracting the appropriate characteristic quantities describing the desired contents of images. In addition, suitable querying, matching, indexing and searching techniques are required.
Content-Based Video Retrieval (CBVR): A process framework for efficiently retrieving required clip from video. The retrieval relies on the organization of video and non-linear search techniques.
Content-Based Visual Information Retrieval (CBVIR): An umbrella including both CBIR and CBVR, as well as retrieval of other visual forms based on the contents they brought.
Tilt: One type of camera moving forms in capturing the scene image. It consists of the movement of camera around the horizontal axis in the imaging plan.