Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  reports a method for acquiring the prior probability of human existence by using past human trajectories and the color of an image. The priors play important roles in human detection as ll as in scene understanding. The proposed method is based on the assumption that a person can exist again in an area where he/she existed in the past. In order to acquire the priors efficiently, a high prior probability is assigned to an area having the same color as past human trajectories.  use a particle filter for representing the prior probability. Therefore,  can represent a complex prior probability using only a few parameters. Through experiments,  confirmed that our proposed method can acquire the prior probability efficiently and it can realize highly accurate human detection using the obtained prior probability.
['Hitoshi Habe', 'Hidehito Nakagawa', 'Masatsugu Kidode']
I am writing a research paper on a idea Efficient acquisition of human existence priors from motion trajectories
[{"from": "human", "value": "I am writing a research paper on a idea Efficient acquisition of human existence priors from motion trajectories"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  reports a method for acquiring the prior probability of human existence by using past human trajectories and the color of an image. The priors play important roles in human detection as ll as in scene understanding. The proposed method is based on the assumption that a person can exist again in an area where he/she existed in the past. In order to acquire the priors efficiently, a high prior probability is assigned to an area having the same color as past human trajectories.  use a particle filter for representing the prior probability. Therefore,  can represent a complex prior probability using only a few parameters. Through experiments,  confirmed that our proposed method can acquire the prior probability efficiently and it can realize highly accurate human detection using the obtained prior probability."}]