The Role of Global Appearance of Omnidirectional Images in Relative Distance and Orientation Retrieval

Román, Vicente; Payá, Luis; Peidró, Adrián; Ballesta, M. Teresa Sánchez; Reinoso, Óscar

doi:10.3390/s21103327

Cited by 3 publications

(1 citation statement)

References 71 publications

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“…Global image descriptors have proven effective for capturing the overall appearance of omnidirectional images [ 27 ]. Earlier works focused on adapting existing, general-purpose feature extraction and matching algorithms.…”

Section: Related Workmentioning

confidence: 99%

Optimizing Appearance-Based Localization with Catadioptric Cameras: Small-Footprint Models for Real-Time Inference on Edge Devices

Rostkowska

Skrzypczyński

2023

Sensors

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This paper considers the task of appearance-based localization: visual place recognition from omnidirectional images obtained from catadioptric cameras. The focus is on designing an efficient neural network architecture that accurately and reliably recognizes indoor scenes on distorted images from a catadioptric camera, even in self-similar environments with few discernible features. As the target application is the global localization of a low-cost service mobile robot, the proposed solutions are optimized toward being small-footprint models that provide real-time inference on edge devices, such as Nvidia Jetson. We compare several design choices for the neural network-based architecture of the localization system and then demonstrate that the best results are achieved with embeddings (global descriptors) yielded by exploiting transfer learning and fine tuning on a limited number of catadioptric images. We test our solutions on two small-scale datasets collected using different catadioptric cameras in the same office building. Next, we compare the performance of our system to state-of-the-art visual place recognition systems on the publicly available COLD Freiburg and Saarbrücken datasets that contain images collected under different lighting conditions. Our system compares favourably to the competitors both in terms of the accuracy of place recognition and the inference time, providing a cost- and energy-efficient means of appearance-based localization for an indoor service robot.

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Section: Related Workmentioning

confidence: 99%

Optimizing Appearance-Based Localization with Catadioptric Cameras: Small-Footprint Models for Real-Time Inference on Edge Devices

Rostkowska

Skrzypczyński

2023

Sensors

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Generating a full spherical view by modeling the relation between two fisheye images

Flores,

Valiente,

Peidró

et al. 2024

Vis Comput

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Full spherical views provide advantages in many applications that use visual information. Dual back-to-back fisheye cameras are receiving much attention to obtain this type of view. However, obtaining a high-quality full spherical view is very challenging. In this paper, we propose a correction step that models the relation between the pixels of the pair of fisheye images in polar coordinates. This correction is implemented during the mapping from the unit sphere to the fisheye image using the equidistant fisheye projection. The objective is that the projections of the same point in the pair of images have the same position on the unit sphere after the correction. In this way, they will also have the same position on the equirectangular coordinate system. Consequently, the discontinuity between the spherical views for blending is minimized. Throughout the manuscript, we show that the angular polar coordinates of the same scene point in the fisheye images are related by a sine function and the radial distance coordinates by a linear function. Also, we propose employing a polynomial as a geometric transformation between the pair of spherical views during the image alignment since the relationship between the matching points of pairs of spherical views is not linear, especially in the top/bottom regions. Quantitative evaluations demonstrate that using the correction step improves the quality of the full spherical view, i.e. IQ MS-SSIM, up to 7%. Similarly, using a polynomial improves the IQ MS-SSIM up to 6.29% with respect to using an affine matrix.

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Environment modeling and localization from datasets of omnidirectional scenes using machine learning techniques

Cebollada

Payá

Peidró

et al. 2023

Neural Comput & Applic

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This work presents a framework to create a visual model of the environment which can be used to estimate the position of a mobile robot by means of artificial intelligence techniques. The proposed framework retrieves the structure of the environment from a dataset composed of omnidirectional images captured along it. These images are described by means of global-appearance approaches. The information is arranged in two layers, with different levels of granularity. The first layer is obtained by means of classifiers and the second layer is composed of a set of data fitting neural networks. Subsequently, the model is used to estimate the position of the robot, in a hierarchical fashion, by comparing the image captured from the unknown position with the information in the model. Throughout this work, five classifiers are evaluated (Naïve Bayes, SVM, random forest, linear discriminant classifier and a classifier based on a shallow neural network) along with three different global-appearance descriptors (HOG, gist, and a descriptor calculated from an intermediate layer of a pre-trained CNN). The experiments have been tackled with some publicly available datasets of omnidirectional images captured indoors with the presence of dynamic changes. Several parameters are used to assess the efficiency of the proposal: the ability of the algorithm to estimate coarsely the position (hit ratio), the average error (cm) and the necessary computing time. The results prove the efficiency of the framework to model the environment and localize the robot from the knowledge extracted from a set of omnidirectional images with the proposed artificial intelligence techniques.

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The Role of Global Appearance of Omnidirectional Images in Relative Distance and Orientation Retrieval

Cited by 3 publications

References 71 publications

Optimizing Appearance-Based Localization with Catadioptric Cameras: Small-Footprint Models for Real-Time Inference on Edge Devices

Optimizing Appearance-Based Localization with Catadioptric Cameras: Small-Footprint Models for Real-Time Inference on Edge Devices

Generating a full spherical view by modeling the relation between two fisheye images

Environment modeling and localization from datasets of omnidirectional scenes using machine learning techniques

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