Design and assessment of a 360° panoramic and high-performance capture system with two tiled catadioptric imaging channels

Song, Weitao; Liu, Xuming; Peng, Lü; Huang, Yetao; Weng, Dongdong; Zheng, Yuanjin; Liu, Yue; Wang, Yongtian

doi:10.1364/ao.57.003429

Cited by 13 publications

(7 citation statements)

References 23 publications

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“…The equidistant fisheye model, implemented in Agisoft Metashape, is not suitable for objects projected in the hyper-hemispheric image field. To circumvent this limitation, Song et al (2018) used equidistant projection combined with a polynomial model. The use of hyperhemispheric points requires further investigations, which will be discussed in future works.…”

Section: Resultsmentioning

confidence: 99%

3d Reconstruction of Citrus Trees Using an Omnidirectional Optical System

Castanheiro

Tommaselli

Campos

et al. 2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. This paper presents a feasibility study on the use of omnidirectional systems for 3D modelling of agricultural crops, aiming a systematic monitoring. Omnidirectional systems with multiple sensors have been widely used in close-range photogrammetry (CRP), which can be a good alternative to provide data for digital agriculture management. The GoPro Fusion dual-camera is the omnidirectional system used in this work. This system is composed of two cameras with fisheye lenses that cover more than 180° each one in back-to-back position. System calibration, camera orientation and 3D reconstruction of an agricultural cultivated area were performed in Agisoft Metashape software. A 360° calibration field based on coded targets (CTs) from Agisoft Metashape software was used to calibrate the omnidirectional system. The 3D reconstruction of an orange orchard was performed using fisheye images taken with GoPro Fusion. The results show the potential of using an omnidirectional system for 3D modelling in agricultural crops, in particular citrus trees. Interior orientation parameters (IOPs) was estimated using Agisoft Metashape target/software with a precision of 9 mm. A 3D reconstruction model of the orange orchard area was obtained with an accuracy of 3.8 cm, which can be considered acceptable for agricultural purposes.

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Section: Resultsmentioning

confidence: 99%

3d Reconstruction of Citrus Trees Using an Omnidirectional Optical System

Castanheiro

Tommaselli

Campos

et al. 2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…Image stitching using two fisheye lenses enables a larger panoramic FoV [42]- [44]. A more compact volume can be obtained by refraction of the optical path using prisms [45], [46]. In the vacuum environment of −40 • C∼ + 60 • C, the space fisheye system can still ensure stable imaging performance [47].…”

Section: B Fisheye Panoramic Systemmentioning

confidence: 99%

Review on Panoramic Imaging and Its Applications in Scene Understanding

Gao¹,

Yang²,

Sheng³

et al. 2022

Preprint

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With the rapid development of high-speed communication and artificial intelligence technologies, human perception of real-world scenes is no longer limited to the use of small Field of View (FoV) and low-dimensional scene detection devices. Panoramic imaging emerges as the next generation of innovative intelligent instruments for environmental perception and measurement. However, while satisfying the need for large-FoV photographic imaging, panoramic imaging instruments are expected to have high resolution, no blind area, miniaturization, and multi-dimensional intelligent perception, and can be combined with artificial intelligence methods towards the next generation of intelligent instruments, enabling deeper understanding and more holistic perception of 360 • real-world surrounding environments. Fortunately, recent advances in freeform surfaces, thinplate optics, and metasurfaces provide innovative approaches to address human perception of the environment, offering promising ideas beyond conventional optical imaging. In this review, we begin with introducing the basic principles of panoramic imaging systems, and then describe the architectures, features, and functions of various panoramic imaging systems. Afterwards, we discuss in detail the broad application prospects and great design potential of freeform surfaces, thin-plate optics, and metasurfaces in panoramic imaging. We then provide a detailed analysis on how these techniques can help enhance the performance of panoramic imaging systems. We further offer a detailed analysis of applications of panoramic imaging in scene understanding for autonomous driving and robotics, spanning panoramic semantic image segmentation, panoramic depth estimation, panoramic visual localization, and so on. Finally, we cast a perspective on future potential and research directions for panoramic imaging instruments.

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“…26 Design strategies and tiling methods of 360-deg panoramic capturing with two channels were analyzed in detail in Ref. 27.…”

Section: Introductionmentioning

confidence: 99%

Design of a 360-deg panoramic capture system based on a smart phone

Song

Liu²,

Cheng

et al. 2020

Opt. Eng.

Self Cite

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A panoramic imaging system has been developed using two afocal lenses and a smart phone that consists of cameras on both sides. An individual afocal lens has been developed with a large field of view (FOV) and a large exit pupil, which can enlarge the FOV of a smart phone camera to above 180 deg. Some issues with the smart phone-based 360-deg panoramic system, such as relative illuminance and assembly tolerance, were analyzed in detail and taken into consideration during the design procedure. A prototype has been developed with a low fabrication cost, yet producing impressive panoramic image quality.

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Design and assessment of a 360° panoramic and high-performance capture system with two tiled catadioptric imaging channels

Cited by 13 publications

References 23 publications

3d Reconstruction of Citrus Trees Using an Omnidirectional Optical System

3d Reconstruction of Citrus Trees Using an Omnidirectional Optical System

Review on Panoramic Imaging and Its Applications in Scene Understanding

Design of a 360-deg panoramic capture system based on a smart phone

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