Automatically Extracting 3D Models and Network Analysis for Indoors
نویسندگان
چکیده
The areas such as emergency services, transportation, security, visitor guiding, etc. are the subjects of 3D network analysis applications. Especially, the problem of evacuating the buildings through the shortest path with safety, has become more important than ever in a case of extraordinary circumstances (i.e. disastrous accidents, massive terrorist attacks) happening in complex and tall buildings of today’s world. This study presents a model which, first, automatically extracts geometry and topology of a building; second, computes the distances among all entities and records them into the geodatabase; and then, investigates the shortest path between two user-specified entities by using 3D network analysis based on modified Dijkstra algorithm. The model also provides a user with a 3D interactive visualization feature. This paper briefly describes the model and presents a simple application, it is described somewhere else in detail.
منابع مشابه
3D Models Recognition in Fourier Domain Using Compression of the Spherical Mesh up to the Models Surface
Representing 3D models in diverse fields have automatically paved the way of storing, indexing, classifying, and retrieving 3D objects. Classification and retrieval of 3D models demand that the 3D models represent in a way to capture the local and global shape specifications of the object. This requires establishing a 3D descriptor or signature that summarizes the pivotal shape properties of th...
متن کاملPrediction of the waste stabilization pond performance using linear multiple regression and multi-layer perceptron neural network: a case study of Birjand, Iran
Background: Data mining (DM) is an approach used in extracting valuable information from environmental processes. This research depicts a DM approach used in extracting some information from influent and effluent wastewater characteristic data of a waste stabilization pond (WSP) in Birjand, a city in Eastern Iran. Methods: Multiple regression (MR) and neural network (NN) models were examined u...
متن کاملApplication of Artificial Neural Networks and Support Vector Machines for carbonate pores size estimation from 3D seismic data
This paper proposes a method for the prediction of pore size values in hydrocarbon reservoirs using 3D seismic data. To this end, an actual carbonate oil field in the south-western part ofIranwas selected. Taking real geological conditions into account, different models of reservoir were constructed for a range of viable pore size values. Seismic surveying was performed next on these models. F...
متن کاملStress Distribution in Four Restorative Methods in Endodontically Treated Maxillary Premolar: A 3D Finite Element Analysis
Introduction: the Restoration of endodontically treated teeth is critical, and the Awareness of stresses developed by oblique and vertical forces in restorative methods take a great role in treatment plans. Due to the anatomical shape and inherent form of the stress distribution premolars, could be lost by fractures. Some fractures such as vertical fracture which is probable in...
متن کاملRevisiting Role Discovery in Networks: From Node to Edge Roles
Previous work in network analysis has focused on modeling the mixed-memberships of node roles in the graph, but not the roles of edges. We introduce the edge role discovery problem and present a generalizable framework for learning and extracting edge roles from arbitrary graphs automatically. Furthermore, while existing node-centric role models have mainly focused on simple degree and egonet f...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2006