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The segmentation into acts of a circus performance video is challenging as the content has similar characteristics to other performance videos but is quite different from movies, TV programs, and home videos. Segmentation is useful as a long duration circus show usually contains several shorter segments that are acts. We propose a new method for detecting end-of-act within circus performance videos. Unlike other temporal video segmentation methods, this method does not rely on shot detection techniques and uses audio and video content analysis separately. First is audio content analysis, for detecting applause on the circus audio stream. Second is image analysis. The applause is further analyzed to test whether this applause occurs at the end-of-act. An end-of-act is detected, if the image(s) before and after the applause are different or there are black frames just after the applause. Otherwise, it is not the end-of-act. The experiment to detect end-of-act on Circus Oz performance videos achieved a 92.27 % recall and 49.05 % precision, providing useful clues that assist human annotators to segment circus video into acts. [authors summary]

Designing a ‘living archive’ that will enable new forms of circus performance to be realised is a complex and dynamic challenge. This paper discusses the methods and approaches used by the research team in the design of the Circus Oz Living archive. Essential to this project has been the design of a responsive methodology that could embrace the diverse areas of knowledge and practice that have led to a design outcome that integrates the affordances of the circus with those of digital technologies. The term ‘living archive’ has been adopted as a means to articulate the dynamic nature of the archive. This is an archive that will always be evolving, not only because of the on going collection of content, but more importantly
because the performance of the archive users will themselves become part of the archive collection. [authors summary]