Analysis of Relationship between Objective Performance Measurement and 3D Visual Discomfort in Depth Map Upsampling

Gil, Jong In; Mahmoudpour, Saeed; Kim, Manbae

doi:10.5909/jbe.2014.19.1.31

Cited by 2 publications

(1 citation statement)

References 11 publications

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“…최근 들어, 사용자에게 몰입감과 깊이감을 제공할 수 있 는 3차원 콘텐츠가 많은 분야에 각광받고 있다 [1] [2] . 최근 들어, 이 러한 문제를 해결하기 위해서 깊이맵에 대응 되는 색상 영 상 정보를 이용하는 기술들이 많이 사용되고 있다 [3,4] .…”

Section: ⅰ 서 론unclassified

Depth Upsampling Method Using Total Generalized Variation

Hong¹,

Ho²

2016

Journal of Broadcast Engineering

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Acquisition of reliable depth maps is a critical requirement in many applications such as 3D videos and free-viewpoint TV. Depth information can be obtained from the object directly using physical sensors, such as infrared ray (IR) sensors. Recently, Time-of-Flight (ToF) range camera including KINECT depth camera became popular alternatives for dense depth sensing. Although ToF cameras can capture depth information for object in real time, but are noisy and subject to low resolutions. Recently, filter-based depth up-sampling algorithms such as joint bilateral upsampling (JBU) and noise-aware filter for depth up-sampling (NAFDU) have been proposed to get high quality depth information. However, these methods often lead to texture copying in the upsampled depth map. To overcome this limitation, we formulate a convex optimization problem using higher order regularization for depth map upsampling. We decrease the texture copying problem of the upsampled depth map by using edge weighting term that chosen by the edge information. Experimental results have shown that our scheme produced more reliable depth maps compared with previous methods.

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Section: ⅰ 서 론unclassified

Depth Upsampling Method Using Total Generalized Variation

Hong¹,

Ho²

2016

Journal of Broadcast Engineering

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Comparison of Objective Metrics and 3D Evaluation Using Upsampled Depth Map

Mahmoudpour¹,

Choi²,

Kim

2015

Journal of Broadcast Engineering

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Depth map upsampling is an approach to increase the spatial resolution of depth maps obtained from a depth camera. Depth map quality is closely related to 3D perception of stereoscopic image, multi-view image and holography. In general, the performance of upsampled depth map is evaluated by PSNR (Peak Signal to Noise Ratio). On the other hand, time-consuming 3D subjective tests requiring human subjects are carried out for examining the 3D perception as well as visual fatigue for 3D contents. Therefore, if an objective metric is closely correlated with a subjective test, the latter can be replaced by the objective metric. For this, this paper proposes a best metric by investigating the relationship between diverse objective metrics and 3D subjective tests. Diverse reference and no-reference metrics are adopted to evaluate the performance of upsampled depth maps. The subjective test is performed based on DSCQS test. From the utilization and analysis of three kinds of correlations, we validated that SSIM and Edge-PSNR can replace the subjective test.

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Analysis of Relationship between Objective Performance Measurement and 3D Visual Discomfort in Depth Map Upsampling

Cited by 2 publications

References 11 publications

Depth Upsampling Method Using Total Generalized Variation

Depth Upsampling Method Using Total Generalized Variation

Comparison of Objective Metrics and 3D Evaluation Using Upsampled Depth Map

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