Segmentation in Corridor Environments: Combining Floor and Ceiling Detection

Automatic segmentation from indoor images has several applications for mobile platforms. We address the problem of corridor segmentation and propose an approach by combining floor and ceiling detection. However, different difficulties may limit the accuracy of the system. To overcome these difficulties, a strategy is used in this paper to evaluate the degree of consistency of ceiling and floor guidelines. The method is based on computing the disparity between the hypothesized vanishing points by intersecting the boundaries par-wise. The approach is evaluated in a novel dataset. Our experimental validation confirms that the integration of floor and ceiling detection with the consistency model performs effectively and robustly. Because of the simplicity of the method, the image processing is quite fast and robust.