Visual Place Representation and Recognition from Depth Images
Not on the map. Why?
Abstract (arXiv)
This work proposes a new method for place recognition based on the scene architecture. From depth video, we compute the 3D model and we derive and describe geometrically the 2D map from which the scene descriptor is deduced to constitute the core of the proposed algorithm. The obtained results show the efficiency and the robustness of the propounded descriptor to scene appearance changes and light variations.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 9 of its 76 references that are in the map. First posted on arXiv 27 Dec 2021.
Builds on
9 of 76 references.
References · 9
- 2015ORB-SLAM: a Versatile and Accurate Monocular SLAM Systemcited by 988
- 2016ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Camerascited by 806
- 2014Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognitioncited by 720
- 2019Robot Localization in Floor Plans Using a Room Layout Edge Extraction Networkcited by 27
- 2020Augmenting Visual Place Recognition with Structural Cuescited by 23
- 2018Learning Effective RGB-D Representations for Scene Recognitioncited by 10
- 2020Visual Localization Using Semantic Segmentation and Depth Predictioncited by 5
- 2016Real-Time Visual Place Recognition for Personal Localization on a Mobile Devicecited by 3
- 2017Complete 3D Scene Parsing from an RGBD Imagecited by 1
Built on by
Citing papers per year: 2023: 2.
2 papers.