mostly implemented in a semi-automatic manner, solving the Building extraction based on pre-established models has been model-image fitting problem based on some high-level inforrecognized as a promising idea for acquiring 3D data for buildmation given by the operator. The spatial data of a building ings from aerial images. This paper proposes a novel building object are determined, when model-image fitting is achieved. extraction method developed from the concept of fitting CSG In contrast to the traditional point-by-point mapping proce-(Constructive Solid Geometry) primitives to aerial images. To dure, model-based building extraction features object-based be practicable, this method adopts a semiautomatic procedata acquisition. Although the idea and benefits of modeldure, carrying out high-level tasks (building detection, model based building extraction have been acknowledged, the workselection, and attribution) interactively by the operator and ing principle is not well established. Therefore, the focus of performing optimal model-image fitting automatically with a this study is to establish a practical theory for model-based least-squares fitting algorithm. Buildings, represented by CSG building extraction. models, can be reconstructed part by part after fitting each Building modeling and model-image fitting are the key parameterized CSG primitive to the edge pixels of aerial issues in model-based building extraction. The issue on buildimages. Reconstructed building parts can then be combined ing modeling is how to establish a set of representative and using CSG Boolean set operators. Consequently, a building is complete building models. This paper reviews some building represented by a CSG tree in which each node links two model schemes known in the field of digital photogrammetry branches of combined parts. This paper demonstrates ten and discusses how CSG modeling is employed in the proposed examples of building extraction from aerial photos taken at a method. The issue in model-image fitting is how to develop a scale of 1:5,000 and scanned at a pixel size of 25 m. All of computer algorithm that is able to determine the pose and the tests were performed in the prototypal system implemented shape parameters of an object model such that the edge lines of in a CAD-based environment cooperated with a number of the wire frame, as projected into the images, are optimally specially designed programs. The process time for each primcoincident with the corresponding edge pixels. It is assumed itive is about 20 seconds and the successful rate of modelthat the image orientations are known and that the pose and image fitting was about 90 percent. Evaluated with some check shape parameters are approximately determined through an points, the fitting accuracy was about 0.3 m horizontally and interactive manual process. To deal with this problem, this 1 m vertically. The test results are encouraging and promote paper proposes a tailored least-squares model-image fitting the theory of model-based building extraction. algori...
Background: We examined the relationships between objectively assessed neighborhood environment and the patterns of sedentary behavior among older adults.Methods: A total of 126 community-dwelling older adults (aged 65 years or above) were recruited. Data on neighborhood environmental attributes (resident density, street intersection density, sidewalk availability, accessible destinations, and accessible public transportation), accelerometer-assessed total time and patterns of sedentary behavior (number and duration of bouts), and sociodemographic characteristics were collected. Multiple linear regression models were developed.Results: After adjustment for potential confounders, greater sidewalk availability was negatively related to the number of sedentary bouts (β = −0.185; 95% CI: −0.362, 0.015; p = 0.034) and sedentary bout duration (β = −0.180; 95% CI: −0.354, −0.011; p = 0.037).Conclusions: This study revealed that a favorable neighborhood environment characterized by sidewalk availability is negatively associated with sedentary behavior patterns in Taiwanese older adults. These findings are critical to inform environmental policy initiatives to prevent sedentary lifestyle in older adults.
ABSTRACT:An automated model-image fitting algorithm is proposed in this paper for generating façade texture image from pictures taken by smartphones or tablet PCs. The façade texture generation requires tremendous labour work and thus, has been the bottleneck of 3D photo-realistic city modelling. With advanced developments of the micro electro mechanical system (MEMS), camera, global positioning system (GPS), and gyroscope (G-sensors) can all be integrated into a smartphone or a table PC. These sensors bring the possibility of direct-georeferencing for the pictures taken by smartphones or tablet PCs. Since the accuracy of these sensors cannot compared to the surveying instruments, the image position and orientation derived from these sensors are not capable of photogrammetric measurements. This paper adopted the least-squares model-image fitting (LSMIF) algorithm to iteratively improve the image's exterior orientation. The image position from GPS and the image orientation from gyroscope are treated as the initial values. By fitting the projection of the wireframe model to the extracted edge pixels on image, the image exterior orientation elements are solved when the optimal fitting achieved. With the exact exterior orientation elements, the wireframe model of the building can be correctly projected on the image and, therefore, the façade texture image can be extracted from the picture.
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