Holovideo: Real-time 3D range video encoding and decoding on GPU

Karpinsky, Nikolaus; Zhang, Song

doi:10.1016/j.optlaseng.2011.08.002

Cited by 26 publications

(35 citation statements)

References 15 publications

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“…It should be noted that Eq. (10) varies sinusoidally to enable lossy compression [1]. Both the aforementioned method and the previously proposed technique [7] utilized a stair image to ensure that the stair changes perfectly align with the 2π discontinuities.…”

Section: B Holoimage Encodingmentioning

confidence: 99%

“…However, the size of 3D range data is drastically larger than that of 2D counterparts. Therefore, storing and transporting 3D range data have become important issues to be dealt with [1].…”

Section: Introductionmentioning

confidence: 99%

“…Inspired by our research on 3D shape measurement with fringe projection techniques, we have recently developed a 3D range data compression technique using Holoimage [6] to convert 3D data into regular 2D images [7], and later extended to 3D range video compression [1]. Specifically, this technique consists in building a virtual fringe projection system called Holoimaging using advanced computer graphics tools to image virtual 3D objects as 2D RGB images, and to further compress 2D images 1559-128X/12/184058-07$15.00/0 © 2012 Optical Society of America with standard 2D compression techniques (e.g., JPG, PNG).…”

Section: Introductionmentioning

confidence: 99%

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Three-dimensional range data compression using computer graphics rendering pipeline

Zhang¹

2012

Appl. Opt.

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This paper presents the idea of naturally encoding three-dimensional (3D) range data into regular twodimensional (2D) images utilizing computer graphics rendering pipeline. The computer graphics pipeline provides a means to sample 3D geometry data into regular 2D images, and also to retrieve the depth information for each sampled pixel. The depth information for each pixel is further encoded into red, green, and blue color channels of regular 2D images. The 2D images can further be compressed with existing 2D image compression techniques. By this novel means, 3D geometry data obtained by 3D range scanners can be instantaneously compressed into 2D images, providing a novel way of storing 3D range data into its 2D counterparts. We will present experimental results to verify the performance of this proposed technique. Disciplines Computer-Aided Engineering and Design | Mechanical Engineering CommentsThis article is from Applied Optics 51 (2012) This paper presents the idea of naturally encoding three-dimensional (3D) range data into regular twodimensional (2D) images utilizing computer graphics rendering pipeline. The computer graphics pipeline provides a means to sample 3D geometry data into regular 2D images, and also to retrieve the depth information for each sampled pixel. The depth information for each pixel is further encoded into red, green, and blue color channels of regular 2D images. The 2D images can further be compressed with existing 2D image compression techniques. By this novel means, 3D geometry data obtained by 3D range scanners can be instantaneously compressed into 2D images, providing a novel way of storing 3D range data into its 2D counterparts. We will present experimental results to verify the performance of this proposed technique.

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Section: B Holoimage Encodingmentioning

confidence: 99%

“…However, the size of 3D range data is drastically larger than that of 2D counterparts. Therefore, storing and transporting 3D range data have become important issues to be dealt with [1].…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Three-dimensional range data compression using computer graphics rendering pipeline

Zhang¹

2012

Appl. Opt.

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“…Classical geometry compression approaches compress the 3D geometry and its attributes, such as normals, texture coordinates, etc., in a model format such as OBJ, PLY, or STL. Though these formats work well for static scans or structured meshes, the same does not hold true for 3D scans from a real-time 3D scanner due to its unstructured nature [3].…”

Section: Introductionmentioning

confidence: 99%

“…Karpinsky and Zhang [9] proposed to utilize the Holoimage technique and Hou et al [10] proposed a similar virtual structured light technique to compress 3D geometry. Based on Holoimage's real-time encoding and decoding, it is able to compress data from real-time 3D scanners [3]. With these merits, it is well suited as a format for high-speed 3D scans, which can then be streamed and stored.…”

Section: Introductionmentioning

confidence: 99%

Three-bit representation of three-dimensional range data

2013

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Our previous research has shown that 3D range data sizes can be substantially reduced if they are converted into regular 2D images using the Holoimage technique. Yet, this technique requires all 24 bits of a standard image to represent one 3D point, making it impossible for a regular 2D image to carry 2D texture information as well. This paper proposes an approach to represent 3D range data with 3 bits, further reducing the data size. We demonstrate that more than an 8.2∶1compression ratio can be achieved with compression root-meansquare error of only 0.34%. Moreover, we can use another bit to represent a black-and-white 2D texture, and thus both 3D data and 2D texture images can be stored into an 8 bit grayscale image. Both simulation and experiments are presented to verify the performance of the proposed technique. Disciplines Computer-Aided Engineering and Design | Mechanical Engineering CommentsThis article is from Applied Optics 52 (2013) Our previous research has shown that 3D range data sizes can be substantially reduced if they are converted into regular 2D images using the Holoimage technique. Yet, this technique requires all 24 bits of a standard image to represent one 3D point, making it impossible for a regular 2D image to carry 2D texture information as well. This paper proposes an approach to represent 3D range data with 3 bits, further reducing the data size. We demonstrate that more than an 8.2∶1 compression ratio can be achieved with compression root-mean-square error of only 0.34%. Moreover, we can use another bit to represent a black-and-white 2D texture, and thus both 3D data and 2D texture images can be stored into an 8 bit grayscale image. Both simulation and experiments are presented to verify the performance of the proposed technique.

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Compression of geometry videos by 3D-SPECK wavelet coder

Bahce

Bayazıt

2020

Vis Comput

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Holovideo: Real-time 3D range video encoding and decoding on GPU

Cited by 26 publications

References 15 publications

Three-dimensional range data compression using computer graphics rendering pipeline

Three-dimensional range data compression using computer graphics rendering pipeline

Three-bit representation of three-dimensional range data

Compression of geometry videos by 3D-SPECK wavelet coder

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