• Current Optics and Photonics
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• v.4 no.6
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• pp.524-529
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• 2020

We propose a depth-fused-type three-dimensional (3D) near-eye display implemented using a birefringent lens set that is made of calcite. By using a birefringent lens and image source (28.70 mm × 21.52 mm), which has different focal lengths according to the polarization state of the incident light, the proposed system can present depth-fused three-dimensional images at 4.6 degrees of field of view (FOV) within 1.6 Diopter (D) to 0.4 D, depending on the polarization distributed depth map. The proposed method can be applied to near-eye displays like head-mounted display systems, for a more natural 3D image without vergence-accommodation conflict.

• Current Optics and Photonics
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• v.4 no.6
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• pp.545-550
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• 2020

We propose a hole-filling method to solve discontinuous depth representation and to reduce the visible seams and cracks that cause the limitation of the viewing angle of the three-dimensional (3D) image in the multilayer type 3D display system. The occlusion and the disocclusion regions between layers, such as the visible seams and cracks, are a major bottleneck of the multilayer type 3D display system to represent a volumetric 3D image by stacking multiple images. As a result, in the reconstructed 3D image, the visible seams and cracks appear as brighter overlapping and undesirable cut-off. In order to resolve the problems above, we applied the depth-fused effect to the sub-depth map generating algorithm and improve the viewing characteristics of the multilayer type 3D display. The experimental demonstrations are also provided to verify the proposed scheme.

• Current Optics and Photonics
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• v.5 no.1
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• pp.32-39
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• 2021

We propose a three-dimensional (3D) streaming system based on a lamina display that can convey field information in real-time by creating floating 3D images that can satisfy the accommodation cue. The proposed system is mainly composed of three parts, namely: a 3D vision camera unit to obtain and provide RGB and depth data in real-time, a 3D image engine unit to realize the 3D volume with a fast response time by using the RGB and depth data, and an optical floating unit to bring the implemented 3D image out of the system and consequently increase the sense of presence. Furthermore, we devise the streaming method required for implementing augmented reality (AR) images by using a multilayered image, and the proposed method for implementing AR 3D video in real-time non-face-to-face communication has been experimentally verified.

• Current Optics and Photonics
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• v.5 no.1
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• pp.23-31
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• 2021

We propose a wheel screen type Lamina 3D display, which realizes a 3D image that can satisfy the accommodation cue by projecting volumetric images encoded by varying polarization states to a multilayered screen. The proposed system is composed of two parts: an encoding part that converts depth information to states of polarization and a decoding part that projects depth images to the corresponded diffusing layer. Though the basic principle of Lamina displays has already been verified by previous studies, those schemes suffered from a bottleneck of inferior resolution of the 3D image due to the blurring on the surfaces of diffusing layers in the stacked volume. In this paper, we propose a new structure to implement the decoding part by adopting a form of the wheel screen. Experimental verification is also provided to support the proposed principle.

• 한국정보디스플레이학회:학술대회논문집
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• 2004.08a
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• pp.440-441
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• 2004

A volumetric three-dimensional (3D) display system was presented, which utilizes a rotating two-dimensional (2D) display panel of light emitting diodes (LEDs) to generate more than 10 million volume pixels (voxels) within a cylindrical volume of 165 mm in height and 292 mm in diameter. Due to persistence of vision, momentarily addressed voxel information is perceived and fused into a 3D image. Important cues for depth perception, such as binocular parallax, accommodation, convergence and motion parallax are satisfied automatically and naturally, thus it is suitable for individual or group viewing, without the need for any special visual aids.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.307-313
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• 2021

In this paper, a lightweight network with fewer parameters compared to the existing object detection method is proposed. In the case of the currently used detection model, the network complexity has been greatly increased to improve accuracy. Therefore, the proposed network uses EfficientNet as a feature extraction network, and the subsequent layers are formed in a pyramid structure to utilize low-level detailed features and high-level semantic features. An attention process was applied between pyramid structures to suppress unnecessary noise for prediction. All computational processes of the network are replaced by depth-wise and point-wise convolutions to minimize the amount of computation. The proposed network was trained and evaluated using the PASCAL VOC dataset. The features fused through the experiment showed robust properties for various objects through a refinement process. Compared with the CNN-based detection model, detection accuracy is improved with a small amount of computation. It is considered necessary to adjust the anchor ratio according to the size of the object as a future study.