Low-latency compression of mocap data using learned spatial decorrelation transform

Hou, Junhui; Chau, Lap-Pui; Thalmann, Nadia Magnenat; He, Ying

doi:10.1016/j.cagd.2016.02.002

Cited by 12 publications

(7 citation statements)

References 28 publications

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“…However, for rendering, we use higher resolution versions of the triangles, in which both the vertices and the colors are interpolated up from V (t) r and C (t) r using Algorithm 6 to obtain higher resolution vertices and colors V (t) rr and C (t) rr . We use the following distortion measures as very close approximations of (15) and (16):…”

Section: ) Triangle Cloud Distortionmentioning

confidence: 99%

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Dynamic polygon clouds: representation and compression for VR/AR

Pavéz

Chou

Queiroz

et al. 2018

SIP

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We introduce the polygon cloud, a compressible representation of three-dimensional geometry (including attributes, such as color), intermediate between polygonal meshes and point clouds. Dynamic polygon clouds, like dynamic polygonal meshes and dynamic point clouds, can take advantage of temporal redundancy for compression. In this paper, we propose methods for compressing both static and dynamic polygon clouds, specifically triangle clouds. We compare triangle clouds to both triangle meshes and point clouds in terms of compression, for live captured dynamic colored geometry. We find that triangle clouds can be compressed nearly as well as triangle meshes, while being more robust to noise and other structures typically found in live captures, which violate the assumption of a smooth surface manifold, such as lines, points, and ragged boundaries. We also find that triangle clouds can be used to compress point clouds with significantly better performance than previously demonstrated point cloud compression methods. For intra-frame coding of geometry, our method improves upon octree-based intra-frame coding by a factor of 5–10 in bit rate. Inter-frame coding improves this by another factor of 2–5. Overall, our proposed method improves over the previous state-of-the-art in dynamic point cloud compression by 33% or more.

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Section: ) Triangle Cloud Distortionmentioning

confidence: 99%

“…[15] is a recent example with many references. Compression typically involves an intra-frame transform to remove spatial redundancy and either temporal prediction (if low latency is required) or a temporal transform (if the entire clip or GOF is available) to remove temporal redundancy, as in [16].…”

Section: Related Workmentioning

confidence: 99%

Dynamic polygon clouds: representation and compression for VR/AR

Pavéz

Chou

Queiroz

et al. 2018

SIP

View full text Add to dashboard Cite

show abstract

“…[14] is a recent example with many references. Compression typically involves an intra-frame transform to remove spatial redundancy and either temporal prediction (if low latency is required) or a temporal transform (if the entire clip or group of frames is available) to remove temporal redundancy, as in [15].…”

Section: Motion Estimationmentioning

confidence: 99%

Dynamic Polygon Clouds: Representation and Compression for VR/AR

Chou¹,

Pavéz²,

Queiroz³

et al. 2016

Preprint

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We introduce the polygon cloud, also known as a polygon set or soup, as a compressible representation of 3D geometry (including its attributes, such as color texture) intermediate between polygonal meshes and point clouds. Dynamic or timevarying polygon clouds, like dynamic polygonal meshes and dynamic point clouds, can take advantage of temporal redundancy for compression, if certain challenges are addressed. In this paper, we propose methods for compressing both static and dynamic polygon clouds, specifically triangle clouds. We compare triangle clouds to both triangle meshes and point clouds in terms of compression, for live captured dynamic colored geometry. We find that triangle clouds can be compressed nearly as well as triangle meshes, while being far more robust to noise and other structures typically found in live captures, which violate the assumption of a smooth surface manifold, such as lines, points, and ragged boundaries. We also find that triangle clouds can be used to compress point clouds with significantly better performance than previously demonstrated point cloud compression methods. In particular, for intra-frame coding of geometry, our method improves upon octree-based intra-frame coding by a factor of 5-10 in bit rate. Inter-frame coding improves this by another factor of 2-5. Overall, our dynamic triangle cloud compression improves over the previous state-of-the-art in dynamic point cloud compression by 33% or more.

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“…Similar results were obtained for other sequences. The signalto-quantization noise ratio (SQNR, defined in (24) in Section V-A) is shown vs. filter length for C3D sequences in Fig. 7(a).…”

Section: Filter Lengthmentioning

confidence: 99%

“…It is shown in [21] that such reordering leads to the concentration of energy in g[n] at low frequencies. Several recent works have explored alternative representations and transformations of MoCap data [24], [25], [26]. The reordered data frame is then predicted either from a long-term reference (LTR) frame or from a short-term reference (STR) frame, and the prediction residual is spatially transformed, quantized, and entropy coded.…”

Section: B Hybrid Mocap Codingmentioning

confidence: 99%

Online MoCap Data Coding With Bit Allocation, Rate Control, and Motion-Adaptive Post-Processing

Kwak

Bajia

2017

IEEE Trans. Multimedia

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Abstract-With the advancements in methods for capturing 3D object motion, motion capture (MoCap) data are starting to be used beyond their traditional realm of animation and gaming in areas such as the arts, rehabilitation, automotive industry, remote interactions, and so on. As the amount of MoCap data increases, compression becomes crucial for further expansion and adoption of these technologies. In this paper, we extend our previous work on low-delay MoCap data compression by introducing two improvements. The first improvement is the bit allocation to long-term and short-term reference MoCap frames, which provides a 10-15% reduction in coded bitrate at the same quality. The second improvement is the post-processing in the form of motion-adaptive temporal low-pass filtering, which is able to provide another 9-13% savings in the bitrate. The experimental results also indicate that the proposed online MoCap codec is competitive with several state-of-the-art offline codecs. Overall, the proposed techniques integrate into a highly effective online MoCap codec that is suitable for low-delay applications, whose implementation is provided alongside this paper to aid further research in the field.

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Low-latency compression of mocap data using learned spatial decorrelation transform

Cited by 12 publications

References 28 publications

Dynamic polygon clouds: representation and compression for VR/AR

Dynamic polygon clouds: representation and compression for VR/AR

Dynamic Polygon Clouds: Representation and Compression for VR/AR

Online MoCap Data Coding With Bit Allocation, Rate Control, and Motion-Adaptive Post-Processing

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