Modeling visual fields using virtual ophthalmoscopy: Incorporating geometrical optics, morphometrics, and 3D visualization to validate an interdisciplinary technique

Cerio, Donald G.; Witmer, Lawrence M.

doi:10.1016/j.visres.2019.11.007

Cited by 10 publications

(6 citation statements)

References 61 publications

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“…Firstly, the texture of the visible part of the clothing is mapped to the corresponding area of the 3D model according to the texture and color of the corresponding position of the image. In the process of image mapping, rotation operation is also needed to adjust the direction processing model, and the rotated image is adapted to the size value of the simulation image [23][24][25]. When the programming operation of image rotation is carried out, the reverse mapping method is adopted.…”

Section: Clothing Texture Color Feature Extractionmentioning

confidence: 99%

[Retracted] Study on 3D Clothing Color Application Based on Deep Learning‐Enabled Macro‐Micro Adversarial Network and Human Body Modeling

Liu

Ren

Qin³

2021

Computational Intelligence and Neuroscience

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In real life, people’s life gradually tends to be simple, so the convenience of online shopping makes more and more research begin to explore the convenience optimization of shopping, in which the fitting system is the research product. However, due to the immaturity of the virtual fitting system, there are a lot of problems, such as the expression of clothing color is not clear or deviation. In view of this, this paper proposes a 3D clothing color display model based on deep learning to support human modeling-driven. Firstly, the macro-micro adversarial network (MMAN) based on deep learning is used to analyze the original image, and then, the results are preprocessed. Finally, the 3D model with the original image color is constructed by using UV mapping. The experimental results show that the accuracy of the MMAN algorithm reaches 0.972, the established three-dimensional model is emotional enough, the expression of the clothing color is clear, and the difference between the color difference and the original image is within 0.01, and the subjective evaluation of volunteers is more than 90 points. The above results show that it is effective to use deep learning to build a 3D model with the original picture clothing color, which has great guiding significance for the research of character model modeling and simulation.

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Section: Clothing Texture Color Feature Extractionmentioning

confidence: 99%

[Retracted] Study on 3D Clothing Color Application Based on Deep Learning‐Enabled Macro‐Micro Adversarial Network and Human Body Modeling

Liu

Ren

Qin³

2021

Computational Intelligence and Neuroscience

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“…For our measures, we captured the skulls in dorsal view at the plane of optic axes and used schematic eyeballs to calculate the visual fields, and to estimate the binocular sections. Schematic eyeballs utilize several simplifying assumptions to estimate the optical performance of the visual apparatus (Cerio & Witmer 2020). Some of these assumptions are known to be slightly inaccurate but are nonetheless useful approximations for assessing optical performance, and can provide theoretical estimates of the peripheral limits of visual fields (Martin 2007).…”

Section: Models and Proceduresmentioning

confidence: 99%

“…The study of the visual abilities of birds, as related to their ecology and evolution, has a long history, and over the past several years, huge amount of data has been collected, mainly quantified as visual fields (Martin 2014, Cerio & Witmer 2020. "In vivo" observations on field are difficult, time and access to living specimens of rare species is extremely limited.…”

Section: Introductionmentioning

confidence: 99%

Aspects of cranial adaptation in foot-propelled diving birds – foraging and visual fields of some piscivorous species

Pecsics,

Csörgő

2023

Ornis Hungarica

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The adaptation to an aquatic lifestyle has occurred several times during the evolution of birds. The transition from a terrestrial to an aquatic lifestyle requires enormous changes in morphology, physiology, and behaviour. In addition to many physical parameters, aquatic foraging is also a limiting factor, despite the fact that aquatic habitats are often rich in food and prey. Despite many previous studies (foraging, physiology, anatomy, ecology, etc.) and a large amount of data regarding piscivore foot-propelled diving birds, our knowledge on the possible relationships between cranial morphology, feeding mechanism, visual abilities and binocularity is still very limited. In this study, we attempt to achieve a deeper understanding of the visual abilities and foraging related attributes of 5 recent and 1 extinct species of foot-propelled diving birds. We attempted to measure the horizontal visual fields of these species using 3D visualization techniques. According to our model, the narrowest horizontal binocular field was measured in Anhinga (Anhinga anhinga), and the widest was measured in the cases of Great Cormorant (Phalacrocorax carbo) and Goosander (Mergus merganser). Our results support the prediction that binocular field variation among aquatic birds is primarily associated with foraging methods and activities.

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“…The absence of optic lobe swellings on the endocasts of both species of Desmatosuchus, combined with the modest size of their orbits, suggests that their visual sense might have been unremarkable, although the discovery of scleral ossicles would help refine our assessments of the visual system because scleral rings provide the best quantitative estimates from the skeleton of such optically important parameters as dimensions of the eyeball, lens, and pupil (Cerio & Witmer, 2020;Choiniere et al, 2021;Hall, 2008Hall, , 2009Schmitz, 2009). This information, combined with the small size of the floccular recess and the moderate size of the semicircular canals of the labyrinth, would suggest that highly coordinated gaze stabilization mechanisms were not present, and that, by extension, these species of Desmatosuchus were probably not especially active or agile animals.…”

Section: Paleobiological Inferencesmentioning

confidence: 99%

New digital braincase endocasts of two species of Desmatosuchus and neurocranial diversity within Aetosauria (Archosauria: Pseudosuchia)

Baczko

Desojo

Gower

et al. 2021

The Anatomical Record

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In the present contribution we revise, figure, and redescribe several isolated braincases of the iconic aetosaur Desmatosuchus from the Placerias Quarry locality, Chinle Formation, Arizona, United States. The detailed study of the isolated braincases from the UCMP collection allowed us to assign them at the species-level and recognize two species of Desmatosuchus for the Placerias Quarry: D. spurensis and D. smalli. The former can be distinguished from the latter by the presence of a transverse sulcus on the parietals, deep median pharyngeal recess on the basisphenoid, almost no gap between the basal tubera and the basipterygoid processes, and the exoccipitals meeting at the midline. The presence of D. smalli at the Placerias Quarry has not been previously reported. Based on the braincases UCMP 27408, 27410, 27407, three new brain endocasts were developed through CT scan images, reconstructing the most complete endocranial casts known for an aetosaur, including the encephalon, cranial nerves, inner ear, and endocranial vasculature. The cranial endocasts also exhibited some differences between both species of Desmatosuchus, with D. spurensis having a distinguishable dural expansion and markedly asymmetric anterior and posterior semicircular canals of the labyrinth. Additionally, the combination of osteological features and the endocranial casts allowed us to identify and discuss the presence of an ossified orbitosphenoid on the anteriormost region of the braincase among aetosaurs. Furthermore, we were able to reinterpret some of the observations made by previous authors on the endocast of the holotype of Desmatosuchus spurensis (UMMP VP 7476) and provide some insight into their neurosensory capabilities.

show abstract

Modeling visual fields using virtual ophthalmoscopy: Incorporating geometrical optics, morphometrics, and 3D visualization to validate an interdisciplinary technique

Cited by 10 publications

References 61 publications

[Retracted] Study on 3D Clothing Color Application Based on Deep Learning‐Enabled Macro‐Micro Adversarial Network and Human Body Modeling

[Retracted] Study on 3D Clothing Color Application Based on Deep Learning‐Enabled Macro‐Micro Adversarial Network and Human Body Modeling

Aspects of cranial adaptation in foot-propelled diving birds – foraging and visual fields of some piscivorous species

New digital braincase endocasts of two species of Desmatosuchus and neurocranial diversity within Aetosauria (Archosauria: Pseudosuchia)

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