Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Because of the increase in terrorist attacks, human identification research has become more popular. Gait recognition is one of biometric recognition techniques that can be accurately used to identify a person, since it is hard to alter the style of movement continuously and permanently. In this work,  propose a new gait recognition technique for freestyle walks using Microsoft Kinect. Since our technique supports freestyle walks, it can be employed to identify a person from a distance. This technique can also be used to collect gait information non-invasively and without a person's awareness. Our proposed technique introduce two new concepts to cope with challenges that come with freestyle walking. First, relative coordinate concept is created to handle the non-fixed observation angle issue. Second, the random subsequence-based sum-rule classification is introduced to handle non-fixed length walks issue. Our proposed technique takes different local characteristics of a walk into consideration. It significantly outperforms baseline technique (Dynamic Time Warping with k-NN with accuracy rate of 92.22%. The results also suggests that a human recognition is better done from observing many small movements and postures than observing one large sequence of walk.
['Nitchan Jianwattanapaisarn', 'Nirattaya Khamsemanan', 'Cholwich Nattee']
I am writing a research paper on a idea Gait Recognition from Freestyle Walks Using Relative Coordinates and Random Subsequence-Based Sum-Rule Classification
[{"from": "human", "value": "I am writing a research paper on a idea Gait Recognition from Freestyle Walks Using Relative Coordinates and Random Subsequence-Based Sum-Rule Classification"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Because of the increase in terrorist attacks, human identification research has become more popular. Gait recognition is one of biometric recognition techniques that can be accurately used to identify a person, since it is hard to alter the style of movement continuously and permanently. In this work,  propose a new gait recognition technique for freestyle walks using Microsoft Kinect. Since our technique supports freestyle walks, it can be employed to identify a person from a distance. This technique can also be used to collect gait information non-invasively and without a person's awareness. Our proposed technique introduce two new concepts to cope with challenges that come with freestyle walking. First, relative coordinate concept is created to handle the non-fixed observation angle issue. Second, the random subsequence-based sum-rule classification is introduced to handle non-fixed length walks issue. Our proposed technique takes different local characteristics of a walk into consideration. It significantly outperforms baseline technique (Dynamic Time Warping with k-NN with accuracy rate of 92.22%. The results also suggests that a human recognition is better done from observing many small movements and postures than observing one large sequence of walk."}]