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Factors Affecting the Sense of Scale in Immersive, Realistic Virtual Reality Space Read chapter Read first chapter

2021 | OriginalPaper | Chapter

Place Inference via Graph-Based Decisions on Deep Embeddings and Blur Detections

Authors : Piotr Wozniak, Bogdan Kwolek

Published in: Computational Science – ICCS 2021

Publisher: Springer International Publishing

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Abstract

Current approaches to visual place recognition for loop closure do not provide information about confidence of decisions. In this work we present an algorithm for place recognition on the basis of graph-based decisions on deep embeddings and blur detections. The graph constructed in advance permits together with information about the room category an inference on usefulness of place recognition, and in particular, it enables the evaluation the confidence of final decision. We demonstrate experimentally that thanks to proposed blur detection the accuracy of scene recognition is much higher. We evaluate performance of place recognition on the basis of manually selected places for recognition with corresponding sets of relevant and irrelevant images. The algorithm has been evaluated on large dataset for visual place recognition that contains both images with severe (unknown) blurs and sharp images. Images with 6-DOF viewpoint variations were recorded using a humanoid robot.

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Metadata
Title
Place Inference via Graph-Based Decisions on Deep Embeddings and Blur Detections
Authors
Piotr Wozniak
Bogdan Kwolek
Copyright Year
2021
Book
Computational Science – ICCS 2021

Print ISBN: 978-3-030-77976-4

Electronic ISBN: 978-3-030-77977-1

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-77977-1_14

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