| In this thesis, a method is presented for the capture and interactive presentation of long-term multi-dimensional time-lapse photography. Time-lapse capture is commonly used for the observation based study of relatively long term phenomena such as plant growth and weather patterns. In terms of filmic devices, the visual time compression effect is complementary to slow motion and is nearly as prevalent. In this project, commonly available camera and computer equipment is used to capture images autonomously with minimal system supervision. A set of images is established, using long term, short interval continuous capture at a fixed position. Results are presented demonstrating dynamic movement within this set using the Microsoft Kinect sensor for Xbox 360 to evaluate participant gestures in real-time. Viewers' tracked movements and positions motivate specific frame selection and playback order, allowing independent navigation through the time-lapse, independently by time of day, time of season, and in any order participants can obtain with their own movement and performance. |
