We consider the problem of learning a representation of both spatial relations and dependencies between objects for indoor scene design.We propose a novel knowledge graph framework based on the entity-relation model f...We consider the problem of learning a representation of both spatial relations and dependencies between objects for indoor scene design.We propose a novel knowledge graph framework based on the entity-relation model for representation of facts in indoor scene design, and further develop a weaklysupervised algorithm for extracting the knowledge graph representation from a small dataset using both structure and parameter learning. The proposed framework is flexible, transferable, and readable. We present a variety of computer-aided indoor scene design applications using this representation, to show the usefulness and robustness of the proposed framework.展开更多
The increasing scale and complexity of 3D scene design work urge an efficient way to understand the design in multi-disciplinary team and exploit the experiences and underlying knowledge in previous works for reuse.Ho...The increasing scale and complexity of 3D scene design work urge an efficient way to understand the design in multi-disciplinary team and exploit the experiences and underlying knowledge in previous works for reuse.However the previous researches lack of concerning on relationship maintaining and design reuse in knowledge level.We propose a novel semantic driven design reuse system,including a property computation algorithm that enables our system to compute the properties while modeling process to maintain the semantic consistency,and a vertex statics based algorithm that enables the system to recognize scene design pattern as universal semantic model for the same type of scenes.With the universal semantic model,the system conducts the modeling process of future design works by suggestions and constraints on operation.The proposed framework empowers the reuse of 3D scene design on both model level and knowledge level.展开更多
基金supported by the National Key R&D Program of China(No.2017YFB1002604)the National Natural Science Foundation of China(No.61772298)+1 种基金a Research Grant of Beijing Higher Institution Engineering Research Centerthe Tsinghua–Tencent Joint Laboratory for Internet Innovation Technology
文摘We consider the problem of learning a representation of both spatial relations and dependencies between objects for indoor scene design.We propose a novel knowledge graph framework based on the entity-relation model for representation of facts in indoor scene design, and further develop a weaklysupervised algorithm for extracting the knowledge graph representation from a small dataset using both structure and parameter learning. The proposed framework is flexible, transferable, and readable. We present a variety of computer-aided indoor scene design applications using this representation, to show the usefulness and robustness of the proposed framework.
基金the National Natural Science Foundation of China(Nos.61073086 and 70871078)the National High Technology Research and Development Program (863) of China(No.2008AA04Z126)
文摘The increasing scale and complexity of 3D scene design work urge an efficient way to understand the design in multi-disciplinary team and exploit the experiences and underlying knowledge in previous works for reuse.However the previous researches lack of concerning on relationship maintaining and design reuse in knowledge level.We propose a novel semantic driven design reuse system,including a property computation algorithm that enables our system to compute the properties while modeling process to maintain the semantic consistency,and a vertex statics based algorithm that enables the system to recognize scene design pattern as universal semantic model for the same type of scenes.With the universal semantic model,the system conducts the modeling process of future design works by suggestions and constraints on operation.The proposed framework empowers the reuse of 3D scene design on both model level and knowledge level.
