NSF Award
9960369
This Small Business Innovative Research Phase I project from the Mostert Group proposes to develop a method to track animals and humans in motion, particularly in athletic events, where movement can be characterized by repetitive motions over a relatively short period of time. An efficient algorithm for tracking of biological motion through cluttered backgrounds and significant self-occlusion that does not require the placement of visual targets, is proposed. While the proposed algorithms will have application in many other domains, the Mostert Group initially focuses on real-time tracking of running subjects over a fixed distance in actual athletic events. Repetitive motions will be exploited by developing mechanisms to learn subsequent search regions for constrained template matching. A small database of tracked positions and velocities (derived from previous motion sequences) will allow the algorithm to generalize to new subjects moving over the same course. The Principal Investigator, Paul Mostert, has created a trailing template method that will be combined with the method of deformable templates of Zhong, Jain, and Dubuisson-Jolly, and used in conjunction with skeletal models that will guide the deformation of the ZJDJ templates through potentially confusing relationships (e.g., the crossover motion of the legs). The primary objectives of Phase I research will be a preliminary development of a graphical user interface followed by that of two key tracking technologies; (1) a predictive algorithm to efficiently guide the search for the next position of the object features within video frames, and (2) a model-based approach to deformation of image templates using skeletal guides to improve tracking robustness of biological motion.<br/><br/>Applications for this software proffered by the Mostert Group have a ready market demand. Present commercial tracking technology of biological motion requires the placement of intrusive control targets at critical positions on the subject. The commercial need for tracking and characterizing general biological motion will be exploited, including tools for animal behavior analysis, and predicting and improving motion efficiency in athletes. An initial vertical market for obtaining statistical measures known to be significant to the future performance of a racehorse has considerable potential.
