Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: 3D sensing hardware, such as the Microsoft Kinect, allows new interaction paradigms that would be difficult to accomplish with traditional RGB cameras alone. One basic step in realizing these new methods of animal-computer interaction is posture and behavior detection and classification. ,  present a system capable of identifying static postures for canines that does not rely on hand-labeled data at any point during the process.  create a model of the canine based on measurements automatically obtained in from the first few captured frames, reducing the burden on users.  also present a preliminary evaluation of the system with five dogs, which shows that the system can identify the "standing," "sitting," and "lying" postures with approximately 70%, 69%, and 94% accuracy, respectively.
['Sean Mealin', 'Ignacio X. Domínguez', 'David L. Roberts']
I am writing a research paper on a idea Semi-supervised classification of static canine postures using the Microsoft Kinect
[{"from": "human", "value": "I am writing a research paper on a idea Semi-supervised classification of static canine postures using the Microsoft Kinect"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: 3D sensing hardware, such as the Microsoft Kinect, allows new interaction paradigms that would be difficult to accomplish with traditional RGB cameras alone. One basic step in realizing these new methods of animal-computer interaction is posture and behavior detection and classification. ,  present a system capable of identifying static postures for canines that does not rely on hand-labeled data at any point during the process.  create a model of the canine based on measurements automatically obtained in from the first few captured frames, reducing the burden on users.  also present a preliminary evaluation of the system with five dogs, which shows that the system can identify the \"standing,\" \"sitting,\" and \"lying\" postures with approximately 70%, 69%, and 94% accuracy, respectively."}]