In this paper, we propose an approach to design recovery of real-time graphical applications -such as flight simulators and games -that uses video to link lowerlevel code events with their higher-level graphical manifestations. Such a link can be used for both top-down and bottom-up design recovery. Top-down, one can identify an interesting visual event in the video and then see which lower-level code event(s) are responsible for it. Bottomup, one can explain code of interest by seeing the sorts of high-level visual events in the video to which that code corresponds. The link between low-level code events and high-level visual events can be established by inspection or through an automated technique.As an example of the latter, clicking on a falling creature in the video would yield code specific to the falling creature -excluding irrelevant code from other walking/climbing creatures at that same moment in the video. We shall demonstrate by example how our design recovery method sheds light on the design of real-time graphical applications.
Voxel reconstruction has received increasing interest in recent times, driven by the need for efficient reconstructions of real world scenes from video images. The voxel model has proven useful for activity recognition and motion capture technologies. However most current voxel reconstruction algorithms operate on a fairly small 3-D real world volume and only allow for a single person to be reconstructed. In this paper we present SparseSPOT, an extension of the SPOT voxel reconstruction algorithm, that enables real-time reconstruction of multiple humans within a large environment. We compare SparseSPOT to SPOT and show (by extensive experimental evaluation) that the former achieves superior real time
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