If “a picture is worth a thousand words,” then a video may be worth a thousand pictures. Videos have been increasingly used in multiple applications, including surveillance, teleconferencing, learning and experience sharing. Since a video captures a scene from a particular viewpoint, it can often be understood better if presented within a larger spatial context. We call such interactive visualizations that combine videos with their spatial context "Contextualized Videos".

Over recent years, multiple innovative Contextualized Video interfaces have been proposed to taking advantage of the latest computer graphics and video processing technologies. These interfaces opened a huge design space with numerous design possibilities, each with its own benefits and limitations. To avoid piecemeal understanding of the design space, this dissertation systematically designs and evaluates Contextualized Video interfaces based on a taxonomy of tasks that can potentially benefit from Contextualized Videos.

This dissertation first formalizes a design space. New designs are created incrementally along the four major dimensions of the design space. These designs are then empirically compared through a series of controlled experiments using multiple tasks. The tasks are carefully selected from a task taxonomy, which helps to avoid piecemeal understanding of the effect of the designs. Our design practices and empirical evaluations result in a set of design guidelines on how to choose proper designs according to the characteristics of the tasks and the users. Finally, we demonstrate how to apply the design guidelines to prototype a complex interface for a specific video surveillance application.