Based on the features of cracks, this research proposes the concept of a crack key point as a method for crack characterization and establishes a model of image crack detection based on the reference anchor points method, named KP-CraNet. Based on ResNet, the last three feature layers are repurposed for the specific task of crack key point feature extraction, named a feature filtration network. The accuracy of the model recognition is controllable and can meet both the pixel-level requirements and the efficiency needs of engineering. In order to verify the rationality and applicability of the image crack detection model in this study, we propose a distribution map of distance. The results for factors of a classical evaluation such as accuracy, recall rate, F1 score, and the distribution map of distance show that the method established in this research can improve crack detection quality and has a strong generalization ability. Our model provides a new method of crack detection based on computer vision technology.
Abstract-In this paper, we proposed an improved saliency computing method based on BING method. We observed that the undetected objects of BING method have something in common-that is, most of them are occluded or truncated. Therefore, we improved BING method by: Firstly, make a new training set with undetected objects (by BING method) and truncated ground truth of the original training set. Then, train an assistant filter on this new training set. The assistant filter supplements BING method by detecting objects which BING method misses successfully. The experimental results show that the detection rate with improved BING method is increased from 97.2% to 98.1% for 2000 proposals, and that our method, with training of an assistant filter, is better than original BING method at finding incomplete objects.
Because the clear height of a building involves many particularities of buildings, structures and equipment, the traditional design mode can only roughly estimate the clear height of a building and cannot fully reflect the distribution of the clear height of the whole building, which is not conducive to designers’ design and optimization of buildings. To solve this problem, the concept of a cloud map of the clear height of buildings was proposed for the first time. Based on Revit software, a BIM-based, automatic building clear height cloud map generation program, which realized the efficient analysis of BIM model clear height and can quickly obtain the building clear height cloud map, was developed, therefore enhancing the clear height analysis function of Revit. Compared with the traditional clear height area analysis color block diagram, the clear height cloud diagram of BIM was more accurate, which provides an effective technical means for designers to comprehensively evaluate the clear heights of buildings.
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