Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents a new methodology for improving the tracking of multiple targets in complex scenes. The new method,Motion Parameter Sharing, incorporates social motion information into tracking predictions. This is achieved by allowing a tracker to share motion estimates within groups of targets which have previously been moving in a coordinated fashion. The method is intuitive and, as ll as aiding the prediction estimates, allows the implicit formation of 'social groups' of targets as a side effect of the process. The underlying reasoning and method are presented, as ll as a description of how the method fits into the framework of a typical Bayesian tracking system. This is follod by some preliminary results which suggest the method is more accurate and robust than algorithms which do not incorporate the social information available in multiple target scenarios.
['Andrew P. French', 'Asad Naeem', 'Ian L. Dryden', 'Tony P. Pridmore']
I am writing a research paper on a idea Using social effects to guide tracking in complex scenes
[{"from": "human", "value": "I am writing a research paper on a idea Using social effects to guide tracking in complex scenes"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents a new methodology for improving the tracking of multiple targets in complex scenes. The new method,Motion Parameter Sharing, incorporates social motion information into tracking predictions. This is achieved by allowing a tracker to share motion estimates within groups of targets which have previously been moving in a coordinated fashion. The method is intuitive and, as ll as aiding the prediction estimates, allows the implicit formation of 'social groups' of targets as a side effect of the process. The underlying reasoning and method are presented, as ll as a description of how the method fits into the framework of a typical Bayesian tracking system. This is follod by some preliminary results which suggest the method is more accurate and robust than algorithms which do not incorporate the social information available in multiple target scenarios."}]