In rate-distortion optimization, the encoder settings are determined by maximizing a reconstruction quality measure subject to constraint on bit rate. One of main challenges this approach is define that can be computed with low computational cost and which correlates well perceptual quality. While several measures fulfil these two criteria have been developed for images video, no such one exists 3D point clouds. We address limitation video-based cloud compression (V-PCC) standard proposing...

3D point clouds have found a wide variety of applications in multimedia processing, remote sensing, and scientific computing. Although most cloud processing systems are developed to improve viewer experiences, little work has been dedicated perceptual quality assessment clouds. In this work, we build new database, namely the Waterloo Point Cloud (WPC) database. contrast existing datasets consisting small-scale low-quality source content constrained viewing angles, WPC database contains 20...

Recently, 3D point cloud is becoming popular due to its capability represent the real world for advanced content modality in modern communication systems. In view of wide applications, especially immersive towards human perception, quality metrics clouds are essential. Existing evaluations rely on a full or certain portion original cloud, which severely limits their applications. To overcome this problem, we propose novel deep learning-based no reference assessment method, namely PQA-Net....

The real-world applications of 3D point clouds have been growing rapidly in recent years, but effective approaches and datasets to assess the quality are largely lacking. In this work, we construct so far largest cloud database with diverse source content distortion patterns, carry out a comprehensive subjective user study. We 20 high quality, realistic, omni-directional contents. then apply downsampling, Gaussian noise, three types compression algorithms create 740 distorted clouds. Based...

Rate distortion optimization plays a very important role in image/video coding. But for 3D point cloud, this problem has not been investigated. In paper, the rate and characteristics of cloud are investigated detail, typical challenging is solved cloud. Specifically, since quality reconstructed depends on both geometry color distortions, we first propose analytical models information video-based compression platform, then solve joint bit allocation based derived models. To maximize...

With the increasing demand of compressing and streaming 3D point clouds under constrained bandwidth, it has become ever more important to accurately efficiently determine quality compressed clouds, so as assess optimize quality-of-experience (QoE) end users. Here we make one first attempts developing a bitstream-based no-reference (NR) model for perceptual assessment without resorting full decoding data stream. Specifically, establish relationship between texture complexity bitrate...

Point clouds are rapidly gaining popularity in many practical applications, and point cloud quality assessment (PCQA) is an important research topic that helps us measure improve the visual experience applications using clouds. Research on full-reference (FR) PCQAs has recently made impressive progress, no-reference (NR) also gradually increased. However, performance of prior NR PCQA methods still suffers from weak generalization ability lower accuracy than FR metrics general. In this work,...

Point cloud perceptual quality assessment plays a critical role in many applications, including compression and communication. We propose PKT-PCQA, point-based no-reference point deep learning network that emulates the human visual system by using progressive knowledge transfer to convert coarse-grained classification into fine-grained prediction task. PKT-PCQA exploits local global features, as well an attention mechanism based on spatial channel modules. Experiments three large independent...

The scope of point cloud (PC) applications is expanding. We propose a no-reference bitstream-layer quality assessment model that eliminates the need for full decoding PC, providing evaluation scores during V-PCC process. Specifically, we illustrate relationship between content diversity (CD) and perceptual coding distortion in lossless geometric coding. Subsequently, attribute by predicting CD using transform energy (TE) texture quantization parameter (TQP). By combining with geometry...

No-reference bitstream-layer models for point cloud quality assessment (PCQA) use the information extracted from a bitstream real-time and nonintrusive monitoring. We propose no-reference model perceptual of video-based compression (V-PCC) encoded clouds. First, we study relationship between coding distortion texture quantization parameter (TQP) when geometry encoding is lossless. The results indicate that depends on complexity (TC). Next, estimate TC using TQP bitrate per pixel (TBPP), both...

<abstract><p>For sparse signal reconstruction (SSR) problem in compressive sensing (CS), by the splitting technique, we first transform it into a continuously differentiable convex optimization problem, and then new self-adaptive gradient projection algorithm is proposed to solve SSR which has fast solving speed pinpoint accuracy when dimension increases. Global convergence of established detail. Without any assumptions, establish global $ R- $linear rate algorithm, result for...

We modify the video-based point cloud compression standard (V-PCC) by mapping patches to seven regions and encoding geometry color video sequences of each region. then propose a coarse fine rate control algorithm for this scheme. The consists two major steps. First, we allocate target bitrate between information. Then, optimize in turn quantization steps region using analytical models distortion. Experimental results eight clouds showed that average percent error our is only 3.7%, its...

Point clouds are subject to various distortions during point cloud processing missions, any of which may lead quality degradation. Consequently, predicting has attracted a lot attention. In this paper, layered projection-based metric (LP-PCQM) is proposed. We layer the distorted and its original version firstly then extract geometry color features layers. The feature obtained using method extracted upon RGB by point-based method. Finally, LP-PCQM weighted linear combination an optimal subset...

Video-based point cloud compression (V-PCC) is a state-of-the-art moving picture experts group (MPEG) standard for compression. V-PCC can be used to compress both static and dynamic clouds in lossless, near or lossy way. Many objective quality metrics have been proposed distorted clouds. Most of these are full-reference that require the original one. However, some real-time applications, not available, no-reference reduced-reference needed. Three main challenges design metric how build set...

Hierarchical structures of labels usually exist in large-scale classification tasks, where can be organized into a tree-shaped structure. The nodes near the root stand for coarser labels, while close to leaves mean finer labels. We label unseen samples from node leaf node, and obtain multigranularity predictions hierarchical classification. Sometimes, we cannot decision due uncertainty or incomplete information. In this case, should stop at an internal rather than going ahead rashly....

No-reference point cloud quality assessment (PCQA) based on bitstreams uses information extracted from the bitstream for monitoring at network nodes. We develop a no-reference PCQA model perceived of Octree-Lifting coded clouds. At first, our research explores essential correlation between subjective visual degradation and texture quantization parameter (TQP) when using lossless geometric coding. Then, we enhance proposed by incorporating complexity (TC) while taking into account dependence...

Abstract In stereoscopic image quality assessment, human visual system has been universally taken into account to detect perceptual characteristics. A novel full‐reference assessment metric by considering both monocular and binocular features of is proposed. particular, a new region segmentation algorithm firstly proposed divide 3D images occluded non‐occluded regions. The just noticeable difference model employed on the regions formulate vision, while applied reveal vision system....

The real-world applications of 3D point clouds have been growing rapidly in recent years, but not much effective work has dedicated to perceptual quality assessment colored clouds. In this work, we first build a large cloud database for subjective and objective We construct 20 high quality, realistic, omni-directional diverse contents. then apply downsampling, Gaussian noise, three types compression algorithms create 740 distorted carry out experiment evaluate the Our statistical analysis...

With the wide applications of colored point cloud in many fields, perceptual quality assessment plays a vital role visual communication systems owing to existence degradations introduced various stages. However, existing assessments ignore mechanism human system (HVS) which has an important impact on accuracy assessment. In this paper, progressive knowledge transfer based perception for clouds (PKT-PCQA) is proposed. The PKT-PCQA merges local features from neighboring regions and global...

With the rapid development of 3D vision applications based on point clouds, cloud quality assessment(PCQA) is becoming an important research topic. However, prior PCQA methods ignore effect local variance across different areas cloud. To take advantage distribution imbalance, we propose a no-reference assessment (NR-PCQA) method with area correlation analysis capability, denoted as COPP-Net. More specifically, split into patches, generate texture and structure features for each patch, fuse...

Recently, point clouds have emerged as a promising research direction for representing 3D visual data in various immersive applications, including augmented reality, self-driving cars and so on. The on cloud quality assessment (PCQA) has received significant attention. Although there are objective PCQA models, their generalization can not satisfy the requirement of practical applications. Obviously, factors should be considered comprehensively model. dependence pertinence features limit...

No-reference bitstream-layer point cloud quality assessment (PCQA) can be deployed without full decoding at any network node to achieve real-time monitoring. In this work, we develop the first PCQA model dedicated Trisoup-Lifting encoded 3D clouds by analyzing bitstreams decoding. Specifically, investigate relationship among texture bitrate per (TBPP), complexity (TC) and quantization parameter (TQP) while geometry encoding is lossless. Subsequently, estimate TC utilizing TQP TBPP. Then,...

No-reference bitstream-layer point cloud quality assessment (PCQA) can be deployed without full decoding at any network node to achieve real-time monitoring. In this work, we focus on the PCQA problem dedicated Octree-RAHT encoding mode. First, address issue that existing databases have a small scale and limited distortion levels, establish WPC5.0 database which is first one mode with of 400 distorted clouds (PCs) including 4 geometric multiplied by 5 attitude levels. Then, propose model...

A novel bitrate model with low complexity is proposed for perceived compression distortion assessment of mobile video resolution, which extremely useful in intermediate network nodes quality monitoring. Without fully decoding, parameters are extracted by bitstream analysing, such as bitrate, frame type, quantisation parameter, DCT coefficient, motion vector. Bitrate regarded an essential parameter meanwhile the bitrate–MOS curve determined content. Respectively, spatial factor estimated...

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