Photorealistic rendering: a survey on evaluation

Kolivand, Hoshang; Sunar, Mohd Shahrizal; Kakh, Samira Y.; Al-Rousan, Riyadh; Ismail, Ismahafezi

doi:10.1007/s11042-018-5834-7

Cited by 6 publications

(4 citation statements)

References 97 publications

(136 reference statements)

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“…The United States applies much of the cost of intelligence in the safe for protecting its economic interest and integrity in contradiction to terrorism threats. The Americans face more risks in terms of security, and with the application of this technology, the United States maximizes safety within the country's sensitive areas (Kolivand et al, 2018). AI assists in reducing contact between humans; therefore, it increases the chances for the operation to detect the terror risks at several levels.…”

Section: Literature Reviewmentioning

confidence: 99%

Challenges and Solution for Artificial Intelligence in Cybersecurity of the USA

Soni

2020

SSRN Journal

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Section: Literature Reviewmentioning

confidence: 99%

Challenges and Solution for Artificial Intelligence in Cybersecurity of the USA

Soni

2020

SSRN Journal

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“…For further evaluation of the existing rendering methods and techniques in computer graphics, Kolivand et al [58] provided an elaborated survey on photorealistic rendering. The study aimed to ease the selection of the appropriate method in each system developed by researchers using classification and systematization among numerous methods.…”

Section: Display and Rendering Techniquesmentioning

confidence: 99%

Real-time Illumination and Visual Coherence for Photorealistic Augmented/Mixed Reality

Alhakamy

Tüceryan

2020

ACM Comput. Surv.

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A realistically inserted virtual object in the real-time physical environment is a desirable feature in augmented reality (AR) applications and mixed reality (MR) in general. This problem is considered a vital research area in computer graphics, a field that is experiencing ongoing discovery. The algorithms and methods used to obtain dynamic and real-time illumination measurement, estimating, and rendering of augmented reality scenes are utilized in many applications to achieve a realistic perception by humans. We cannot deny the powerful impact of the continuous development of computer vision and machine learning techniques accompanied by the original computer graphics and image processing methods to provide a significant range of novel AR/MR techniques. These techniques include methods for light source acquisition through image-based lighting or sampling, registering and estimating the lighting conditions, and composition of global illumination. In this review, we discussed the pipeline stages with the details elaborated about the methods and techniques that contributed to the development of providing a photo-realistic rendering, visual coherence, and interactive real-time illumination results in AR/MR.

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“…Evaluation of realism in photorealistic rendering has been oriented towards appearance and was used to assess the subjective experience of a viewer (Kolivand, Sunar, Kakh, Al-Rousan and Ismail [12], Greenberg et al [13]). The reason likely lies in the fact that recreating the same environment is a challenging process.…”

Section: Related Workmentioning

confidence: 99%

Image Synthesis Pipeline for Surface Inspection

Bosnar¹,

Saric²,

Dutta³

et al. 2020

Preprint

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Surface inspection development requires large amounts of image data representing the inspected product surface. The image data should contain both the ideal surface and the defective surface that can appear during production. Although image synthesis comes as a natural solution to this problem, its application is not straightforward in automated surface inspection environments. The reason for that is a lot of manual work that should be done for creating defects, simulating the inspection environment, and setting up the acquisition system for validation of simulation. To address these issues, we present a novel pipeline that automatizes surface defect creation, provides realistic rendering in a predefined inspection environment setup, and an acquisition system that enables comparison with the real images. The pipeline creates geometry-imprinted defects which combined with physically based rendering methods enable realistic light response for different light and camera positions during image synthesis. Finally, synthesized images can becompared with the real image taken in the same setup enabling verification. Also, synthesized images enable the visualization of visible surfaces and defects for a given inspection plan.

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Photorealistic rendering: a survey on evaluation

Abstract: The version presented here may differ from the published version or from the version of the record. Please see the repository URL above for details on accessing the published version and note that access may require a subscription.

Cited by 6 publications

References 97 publications

Challenges and Solution for Artificial Intelligence in Cybersecurity of the USA

Challenges and Solution for Artificial Intelligence in Cybersecurity of the USA

Real-time Illumination and Visual Coherence for Photorealistic Augmented/Mixed Reality

Image Synthesis Pipeline for Surface Inspection

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