During continuous development of computer graphics and human-computer interaction,digital three-dimensional(3D)scenes have played a vital role in the academy and industry.3D scenes show graphical rendering results,supply the environment for applications,and provide a foundation for interaction.Despite being common occur-rences,indoor scenes are important.To increase players'gaming experience,indoor game designers require all kinds of aesthetic digital 3D scenes.In online scene decoration,designers also need to predesign the decoration and furniture lay-out preview by interacting with 3D scenes.In studies of virtual reality,we can synthesize virtual space from a digital 3D scene,such as the synthesis of training data for wheelchair users.However,a number of difficulties still need to be over-come to obtain ideal digital 3D scenes for the applications mentioned above.First,manually synthesized 3D scenes are usu-ally time consuming and require considerable experience.Designers must add objects to a scene and adjust their location and orientation one by one.These trivialities but heavy works cause difficulty in focusing on core ideas.Second,digital 3D scene is a data structure with extremely complex structure,and no unified consensus has been given to its data structure.Thus,digital 3D scenes are difficult to obtain and apply in large quantities compared with traditional data structures,such as image,audio or text.To solve the problems mentioned above,some existing work attempted to allow computers to auto-matically synthesize 3D scenes or interactively help synthesize scenes.This survey summarizes these works.This survey also investigates and summarizes 3D digital scene synthesis methodologies from three aspects:automatic scene synthesis,scene synthesis with multichannel and rich input,and interactive scene synthesis.The automatic synthesis allows the com-puter to directly build an indoor layout based on few inputs,such as the contour of the room or the list of objects.Initially,the scene is synthesized by manually setting rules and applying optimizers in an attempt to satisfy these rules.However,the situation increases in complexity during the synthesis practice,and thus,listing all the rules becomes impossible.As the amount of digital indoor scene increases,more works are introducing machine learning methods to study priors from the digital scenes of the 3D indoor scene dataset.Most of these works organize the furniture with graph to apply algorithms on the graph to process with the information.The results outperform those of former works.Researchers have been applying deep learning(DL)technology,such as convolutional neural network and generative adversarial network,to indoor scene synthesis,which strongly improves the synthetic effect.The synthesis with multichannel and rich input aims to synthesize a digital indoor 3D scene with unformatted information,such as image,text,RGBD scan,point cloud,etc.These algo-rithms enable the convenient formation of digital copies of scenes in the real world because they are mainly recorded by pho-tos or literal description.Compared with the works on automatic synthesis,the scene syntheses with multichannel and rich input do not require diversity or aesthetics.However,this type of synthesis needs an algorithm for the accurate reconstruc-tion of the indoor scene in the digital world.The interactive synthesis aims to let users control the process of computer-aided scene synthesis.The related works can mainly be divided into two parts:active and passive interactive syntheses.Active interactive synthesis simultaneously provides designers with suggestions while they synthesizing a scene.If the scene syntheses program can analyze the designers'interaction and recommend the options with higher possibility to be cho-sen,considerable workload can be saved.During passive interactive synthesis,the system learns the user's personal pref-erences from aspects,such as their behavior trajectory,personal abilities,work habits,and height information and auto-matically synthesize scenes that match the user's preferences as much as possible.Eventually,this survey will also summa-rize the application scenario and core technology of the papers and introduce other typical application scenarios and future challenges.We summarized and classified the recent studies on applications of digital 3D scene synthesis to form this sur-vey.Digital 3D indoor scene synthesis has attained great progress and has a wide prospect.The automatic scene synthesis has generally achieved its goal,and more attention should focused on the proposal and resolution of sub-problems and related issues afterward.For scene synthesis with rich input,existing work has explored inputs,such as image,RGBD-scan,text,and sketches.In the future,more potential input forms,such as music and symbols,should be explored.For scene interactive synthesis,current interactions are still limited to mouse and keyboard inputs,and methods based on inter-active scenes,such as virtual reality,augmented reality,and hybrid reality,still need to be explored.Scene synthesis algorithm has continuously broadened its application.Industries normally require the automatic synthesis of a large amount of indoor scenes.The synthetic efficiency can be strongly increased if a computer can provide suggestions regarding an object and its layout.In academic studies,3D scenes are usually applied to form all kinds of dataset.By rendering a scene's photos from various perspectives and channels,researchers can easily obtain images.However,the study on indoor scene synthesis is still facing a number of limitations.The dissimilarity of data structure causes difficulty in extend-ing the work of others.Copyright issues prevent a scene dataset from being freely used by researchers and coders.In the future,indoor scene datasets with additional furniture model and room contour will serve as the basis of indoor scene synthe-sis studies.Numerous related fields,such as style consistency and automatic photography,are also showing progress.
indoor scene3D scene synthesis3D scene interaction3D scene intelligent editingcomputer graphics
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