학술논문

Sketch/Image-Based 3D Scene Retrieval: Benchmark, Algorithm, Evaluation
Document Type
Conference
Source
2019 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR) MIPR Multimedia Information Processing and Retrieval (MIPR), 2019 IEEE Conference on. :264-269 Mar, 2019
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Geoscience
Robotics and Control Systems
Signal Processing and Analysis
Conferences
Information processing
3D scene retrieval
benchmark
sketch based 3D scene retrieval
image based 3D scene retrieval
performance evaluation
Language
Abstract
Sketch/Image-based 3D scene retrieval is to retrieve man-made 3D scene models given a user's hand-drawn 2D scene sketch or a 2D scene image usually captured by a camera. It is a brand new but also very challenging research topic in the field of 3D object retrieval due to the semantic gap in their representations: 3D scene models or views differ from either non-realistic 2D scene sketches or realistic 2D scene images. Due to the intuitiveness in sketching and ubiquitous availability in image capturing, this research topic has vast applications such as 3D scene reconstruction, autonomous driving cars, 3D geometry video retrieval, and 3D AR/VR entertainment. To boost this interesting and important research, we build the currently largest and most comprehensive 2D scene sketch/image-based 3D scene retrieval benchmark1, develop a convolutional neural network (CNN)-based 3D scene retrieval algorithm and finally conduct an evaluation on the benchmark.