Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents a multi-frame data association algorithm for tracking multiple targets in video sequences. Multi-frame data association involves finding the most probable correspondences beten target tracks and measurements (collected over multiple time instances) as ll as handling the common tracking problems such as, track initiations and terminations, occlusions, and noisy detections. The problem is known to be NP-Hard for more than two frames. A rank constrained continuous formulation of the problem is presented that can be efficiently solved using nonlinear optimization methods. It is shown that the global and local extrema of the continuous problem respectively coincide with the maximum and the maximal solutions of the discrete counterpart. A scanning window based tracking algorithm is developed using the formulation that performs ll under noisy conditions with frequent occlusions and multiple track initiations and terminations. The above claims are supported by experiments and quantitative evaluations using both synthetic and real data under different operating conditions.
['Khurram Shafique', 'Mun Wai Lee', 'Niels Haering']
I am writing a research paper on a idea A rank constrained continuous formulation of multi-frame multi-target tracking problem
[{"from": "human", "value": "I am writing a research paper on a idea A rank constrained continuous formulation of multi-frame multi-target tracking problem"}, {"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 multi-frame data association algorithm for tracking multiple targets in video sequences. Multi-frame data association involves finding the most probable correspondences beten target tracks and measurements (collected over multiple time instances) as ll as handling the common tracking problems such as, track initiations and terminations, occlusions, and noisy detections. The problem is known to be NP-Hard for more than two frames. A rank constrained continuous formulation of the problem is presented that can be efficiently solved using nonlinear optimization methods. It is shown that the global and local extrema of the continuous problem respectively coincide with the maximum and the maximal solutions of the discrete counterpart. A scanning window based tracking algorithm is developed using the formulation that performs ll under noisy conditions with frequent occlusions and multiple track initiations and terminations. The above claims are supported by experiments and quantitative evaluations using both synthetic and real data under different operating conditions."}]