@InProceedings{Diniz:2022:3DPoQu,
               author = "Diniz, Rafael",
          affiliation = "{Universidade de Bras{\'{\i}}lia}",
                title = "3D Point-Cloud Quality Assessment Using Color and Geometry Texture 
                         Descriptors",
            booktitle = "Proceedings...",
                 year = "2022",
         organization = "Conference on Graphics, Patterns and Images, 35. (SIBGRAPI)",
             keywords = "point cloud quality assessment, point cloud texture descriptor.",
             abstract = "Since the mid-20th century, the use of digital formats for visual 
                         content allowed a great evolution in how society communicates. The 
                         Internet and digital broadcast systems introduced in the decade 90 
                         to the wider public allowed an incredible expansion of multimedia 
                         consumption by the people, while the telecommunication networks 
                         and providers were pushed to their limits to address the growing 
                         multimedia content demand. Older electronic imaging systems, 
                         notably TV broadcasting systems, were designed after long 
                         subjective quality analysis for the definition of parameters like 
                         the number of lines of the video. But recent digital visual 
                         content services need faster and more affordable ways of 
                         evaluating the human perceived quality of the always-evolving 
                         multimedia systems. To address the need for automatic quality 
                         assessment, in the past decades many visual quality models based 
                         on algorithms that run on digital computers have been proposed. 
                         While the existing models are remarkably advanced for 2D digital 
                         imagery, a new set of immersive media is dawning, with different 
                         data structures, to which the 2D methods are not applicable, and 
                         need novel quality assessment metrics. These novel dawning 
                         immersive media formats provide a 3D visual representation of real 
                         objects and scenes. In this new visual format, objects can be 
                         captured, compressed, transmitted, and visualized in real-time not 
                         anymore as a flat 2D image, but as 3D content, allowing 
                         free-viewpoint selection by a consumer of such media. One of the 
                         most popular formats for immersive media is Point Cloud (PC), 
                         which is composed of points with 3 geometry coordinates plus color 
                         information, and sometimes, other information like reflectance and 
                         transparency. This work presents a research on the quality 
                         assessment of 3D PC based on novel color and geometric texture 
                         statistics. Considering that distortions to both color and 
                         geometry attributes of 3D visual content affect the perceived 
                         visual quality, it is proposed in this work to use both 
                         color-based and geometry-based texture descriptors for PC to 
                         obtain the visual degradation through their statistics. This work 
                         introduces 4 novels PC texture descriptors, 3 of them color-based, 
                         while 1 is geometry-based. Also, a new voxelization method is 
                         proposed, which converts points to voxels (volume elements), and 
                         improves the performance of the color- based texture descriptors. 
                         The performance of the proposed PC quality assessment method is 
                         among the best of the state-of- the-art PC quality assessment 
                         methods while being flexible and extensible to adapt to different 
                         types of distortions.",
  conference-location = "Natal, RN",
      conference-year = "24-27 Oct. 2022",
             language = "en",
                  ibi = "8JMKD3MGPEW34M/47QD5CH",
                  url = "http://urlib.net/ibi/8JMKD3MGPEW34M/47QD5CH",
           targetfile = "thesis_paper.pdf",
        urlaccessdate = "2024, Apr. 29"
}