Indoor Scene Recognition via Object Detection and TF-IDF

Author:

Heikel Edvard,Espinosa-Leal LeonardoORCID

Abstract

Indoor scene recognition and semantic information can be helpful for social robots. Recently, in the field of indoor scene recognition, researchers have incorporated object-level information and shown improved performances. This paper demonstrates that scene recognition can be performed solely using object-level information in line with these advances. A state-of-the-art object detection model was trained to detect objects typically found in indoor environments and then used to detect objects in scene data. These predicted objects were then used as features to predict room categories. This paper successfully combines approaches conventionally used in computer vision and natural language processing (YOLO and TF-IDF, respectively). These approaches could be further helpful in the field of embodied research and dynamic scene classification, which we elaborate on.

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Radiology, Nuclear Medicine and imaging

Reference43 articles.

1. Seeing the Un-Scene: Learning Amodal Semantic Maps for Room Navigation;Narasimhan;arXiv,2020

2. An Indoor Room Classification System for Social Robots via Integration of CNN and ECOC

3. Learning to use topological memory for visual navigation;Kwon;Proceedings of the 20th International Conference on Control, Automation and Systems,2020

4. Target-driven visual navigation in indoor scenes using deep reinforcement learning;Zhu;Proceedings of the IEEE International Conference on Robotics and Automation,2017

5. Indoor scene modeling from a single image using normal inference and edge features

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