Place Recognition in Gardens by Learning Visual Representations: Data Set and Benchmark Analysis

María Leyva-Vallina*, Nicola Strisciuglio, Nicolai Petkov

*Bijbehorende auteur voor dit werk

Onderzoeksoutput: Conference contributionAcademicpeer review

2 Citaten (Scopus)
82 Downloads (Pure)


Visual place recognition is an important component of systems for camera localization and loop closure detection. It concerns the recognition of a previously visited place based on visual cues only. Although it is a widely studied problem for indoor and urban environments, the recent use of robots for automation of agricultural and gardening tasks has created new problems, due to the challenging appearance of garden-like environments. Garden scenes predominantly contain green colors, as well as repetitive patterns and textures. The lack of available data recorded in gardens and natural environments makes the improvement of visual localization algorithms difficult. In this paper we propose an extended version of the TB-Places data set, which is designed for testing algorithms for visual place recognition. It contains images with ground truth camera pose recorded in real gardens in different seasons, with varying light conditions. We constructed and released a ground truth for all possible pairs of images, indicating whether they depict the same place or not. We present the results of a benchmark analysis of methods based on convolutional neural networks for holistic image description and place recognition. We train existing networks (i.e. ResNet, DenseNet and VGG NetVLAD) as backbone of a two-way architecture with a contrastive loss function. The results that we obtained demonstrate that learning garden-tailored representations contribute to an improvement of performance, although the generalization capabilities are limited.

Originele taal-2English
TitelComputer Analysis of Images and Patterns - 18th International Conference, CAIP 2019, Proceedings
RedacteurenMario Vento, Gennaro Percannella
UitgeverijSpringer Verlag
Aantal pagina's12
ISBN van elektronische versie978-3-030-29888-3
ISBN van geprinte versie978-3-030-29887-6
StatusPublished - sep.-2019
Evenement18th International Conference on Computer Analysis of Images and Patterns, CAIP 2019 - Salerno, Italy
Duur: 3-sep.-20195-sep.-2019

Publicatie series

NaamLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN van geprinte versie0302-9743
ISSN van elektronische versie1611-3349


Conference18th International Conference on Computer Analysis of Images and Patterns, CAIP 2019

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