Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Any mobility aid for the visually impaired people should be able to accurately detect and warn about nearly obstacles. ,  present a method for support system to detect obstacle in indoor environment based on Kinect sensor and 3D-image processing. Color-Depth data of the scene in front of the user is collected using the Kinect with the support of the standard framework for 3D sensing OpenNI and processed by PCL library to extract accurate 3D information of the obstacles. The experiments have been performed with the dataset in multiple indoor scenarios and in different lighting conditions. Results shod that our system is able to accurately detect the four types of obstacle: walls, doors, stairs, and a residual class that covers loose obstacles on the floor. Precisely, walls and loose obstacles on the floor are detected in practically all cases, whereas doors are detected in 90.69% out of 43 positive image samples. For the step detection,  have correctly detected the upstairs in 97.33% out of 75 positive images while the correct rate of downstairs detection is lor with 89.47% from 38 positive images. Our method further allows the computation of the distance beten the user and the obstacles.
['Huy-Hieu Pham', 'Thi-Lan Le', 'Nicolas Vuillerme']
I am writing a research paper on a idea Real-Time Obstacle Detection System in Indoor Environment for the Visually Impaired Using Microsoft Kinect Sensor
[{"from": "human", "value": "I am writing a research paper on a idea Real-Time Obstacle Detection System in Indoor Environment for the Visually Impaired Using Microsoft Kinect Sensor"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Any mobility aid for the visually impaired people should be able to accurately detect and warn about nearly obstacles. ,  present a method for support system to detect obstacle in indoor environment based on Kinect sensor and 3D-image processing. Color-Depth data of the scene in front of the user is collected using the Kinect with the support of the standard framework for 3D sensing OpenNI and processed by PCL library to extract accurate 3D information of the obstacles. The experiments have been performed with the dataset in multiple indoor scenarios and in different lighting conditions. Results shod that our system is able to accurately detect the four types of obstacle: walls, doors, stairs, and a residual class that covers loose obstacles on the floor. Precisely, walls and loose obstacles on the floor are detected in practically all cases, whereas doors are detected in 90.69% out of 43 positive image samples. For the step detection,  have correctly detected the upstairs in 97.33% out of 75 positive images while the correct rate of downstairs detection is lor with 89.47% from 38 positive images. Our method further allows the computation of the distance beten the user and the obstacles."}]