Semi-automatic Depth Map Extraction Method for Stereo Video Conversion

Tsai, Tsung‐Han; Fan, Chen-Shuo; Huang, Chih Yuan

doi:10.1109/icgec.2012.131

Cited by 3 publications

(5 citation statements)

References 11 publications

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“…However, a 2D-to-3D rendering approach that uses only one of these features may not be widely applicable. Therefore, 2D-to-3D rendering approaches that use mixed features have been employed [27][28][29]. The CGDMs calculated by the mixed-features-based method are more stable than that by single-feature-based method.…”

Section: Introductionmentioning

confidence: 99%

Holographic 3D Display Using Depth Maps Generated by 2D-to-3D Rendering Approach

Sui

Cao

2021

Applied Sciences

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Holographic display has the potential to be utilized in many 3D application scenarios because it provides all the depth cues that human eyes can perceive. However, the shortage of 3D content has limited the application of holographic 3D displays. To enrich 3D content for holographic display, a 2D to 3D rendering approach is presented. In this method, 2D images are firstly classified into three categories, including distant view images, perspective view images and close-up images. For each category, the computer-generated depth map (CGDM) is calculated using a corresponding gradient model. The resulting CGDMs are applied in a layer-based holographic algorithm to obtain computer-generated holograms (CGHs). The correctly reconstructed region of the image changes with the reconstruction distance, providing a natural 3D display effect. The realistic 3D effect makes the proposed approach can be applied in many applications, such as education, navigation, and health sciences in the future.

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Section: Introductionmentioning

confidence: 99%

Holographic 3D Display Using Depth Maps Generated by 2D-to-3D Rendering Approach

Sui

Cao

2021

Applied Sciences

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“…Vanishing line detection [10][11][12][13] Depth from model Color theory [14,15,23,34] Depth from defocus Use blur information to get depth value [16][17][18][19] Depth from visual saliency Estimation in region of interest [20][21][22] 5. Four kinds of scanning modes to fix the depth map; 6.…”

Section: Overview Of the Proposed Methodsmentioning

confidence: 99%

“…Battiato [10] proposed a method based on the position of the lines and the vanishing points to derive a suitable assignment of depth. In [12] they gave a semi-automatic method aimed to generate stereoscopic views estimating depth information from a single input video frame and to decrease computation resources. Depth from a model is also used to estimate the depth value in [14,15].…”

Section: Introductionmentioning

confidence: 99%

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A novel method for 2D-to-3D video conversion based on boundary information

Tsai

Huang

Wang

2018

J Image Video Proc.

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This paper proposes a novel method for 2D-to-3D video conversion, based on boundary information to automatically generate the depth map. First, we use the Gaussian model to detect foreground objects and then separate the foreground and background. Second, we employ the superpixel algorithm to find the edge information. According to the superpixels, we will assign corresponding hierarchical depth value to initial depth map. From the result of depth value assignment, we detect the edges by Sobel edge detection with two thresholds to strengthen edge information. To identify the boundary pixels, we use a thinning algorithm to modify edge detection. Following these results, we assign the depth value of foreground to refine it. We use four kinds of scanning path for the entire image to create a more accurate depth map. After that, we have the final depth map. Finally, we utilize depth image-based rendering (DIBR) to synthesize left and right view images. After combining the depth map and the original 2D video, a vivid 3D video is produced.

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“…For the purpose of stereoscopic 3D conversion, Phan et al [15] proposed the module to alleviate much user input, as only the first frame needs to be marked. As in semiautomatic conversion approach, we had some previous result for static background scene [16]. The main concept for this design is based on the vanishing point detection for depth map realization.…”

Section: Related Workmentioning

confidence: 99%

Monocular vision-based depth map extraction method for 2D to 3D video conversion

Tsai¹,

Fan²

2016

J Image Video Proc.

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Due to the demand of 3D visualization and lack of 3D video content, a method converting the 2D to 3D video plays an important role. In this paper, a low-cost and high efficiency post processing method is presented to enjoy the vivid 3D video. We present two semi-automatic depth map extraction methods for stereo video conversion. For the static background video sequence, we proposed a method which combined the foreground segmentation with vanishing line technology. According to the separated foreground and background results from foreground segmentation algorithm, the viewer can use their acquired visual experience to initiate this operation with some depth information of background. Moreover, we proposed another conversion method for the dynamic background video sequence. Foreground segmentation was replaced by the relative velocity estimation based on the motion estimation and motion compensation. Combining the depth map from this work and the original 2D video, a vivid 3D video is produced.

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Semi-automatic Depth Map Extraction Method for Stereo Video Conversion

Cited by 3 publications

References 11 publications

Holographic 3D Display Using Depth Maps Generated by 2D-to-3D Rendering Approach

Holographic 3D Display Using Depth Maps Generated by 2D-to-3D Rendering Approach

A novel method for 2D-to-3D video conversion based on boundary information

Monocular vision-based depth map extraction method for 2D to 3D video conversion

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