Visual analytics tool for proctoring online exams
US-2022392226-A1 · Dec 8, 2022 · US
US2021304354A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2021304354-A1 |
| Application number | US-201917259861-A |
| Country | US |
| Kind code | A1 |
| Filing date | Jul 12, 2019 |
| Priority date | Jul 13, 2018 |
| Publication date | Sep 30, 2021 |
| Grant date | — |
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There is provided a scalable point cloud encoding/decoding method and apparatus. The scalable point cloud decoding method comprises: acquiring an encoded texture image, an encoded geometry image, encoded occupancy map information, and encoded auxiliary patch-info information from a bitstream; acquiring a decoded texture image for each partition using the encoded texture image; reconstructing a geometry image of at least one item selected from among the encoded geometry image, the encoded occupancy map information, and the encoded auxiliary catch-info information; and reconstructing a point cloud using the texture images for the respective partitions and the geometry image.
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1 . A scalable point cloud decoding method comprising: acquiring an encoded texture image, an encoded geometry image, encoded occupancy map information, and encoded auxiliary patch-info information from a bitstream; acquiring a decoded texture image for each partition using the encoded texture image; reconstructing a geometry image of at least one item selected from among the encoded geometry image, the encoded occupancy map information, and the encoded auxiliary patch-info information; and reconstructing a point cloud using the texture images for the respective partitions and the geometry image. 2 . The method according to claim 1 , wherein the partition includes at least one item selected from among a slice, a tile, a tile group, and a brick. 3 . The method according to claim 1 , wherein the reconstructing of the geometry image comprises acquiring a decoded geometry image for each partition using the encoded geometry image. 4 . The method according to claim 1 , wherein the reconstructing of the geometry image comprises generating decoded occupancy map information for each partition using the encoded occupancy map information. 5 . The method according to claim 1 , wherein the reconstructing of the geometry image comprises generating decoded auxiliary patch-info information for each partition using the encoded auxiliary patch-info information. 6 . The method according to claim 1 , wherein the reconstructing of the geometry image comprises smoothing the geometry image. 7 . The method according to claim 1 , further comprising decoding information indicating whether partitioning is applied to the point cloud acquired from the bitstream. 8 . The method according to claim 7 , further comprising decoding at least one type of information among 3D bounding box information and 2D bounding box information on the basis of the information indicating whether the partitioning is applied. 9 . The method according to claim 8 , wherein at least one type of information among the information indicating the partitioning is applied, the 3D bounding box information, and the 2D bounding box information is signaled via header information. 10 . The method according to claim 3 , wherein at least one type of information among the information indicating the partitioning is applied, the 3D bounding box information, and the 2D bounding box information is signaled via SEI message information. 11 . The method according to claim 1 , further comprising decoding mapping information indicating a mapping relation among the texture image, the geometry image, the occupancy map information, and the auxiliary patch-info information. 12 . A point cloud encoding method comprising: dividing a point cloud into at least one partition; encoding at least one partition among the partitions using information on the partition; and encoding the information on the partition. 13 . The method according to claim 12 , wherein the partition includes at least one item selected from among a slice, a tile, a tile group, and a brick. 14 . The method according to claim 12 , wherein the encoding of the partition comprises generating a geometry image in which each of the partitions are padded with geometry image information. 15 . The method according to claim 12 , wherein the encoding of the partition comprises generating a texture image in which each of the partitions is padded with texture image information. 16 . The method according to claim 12 , wherein the encoding of the partition comprises encoding occupancy map information for each of the partitions. 17 . The method according to claim 12 , wherein the encoding of the partition comprises encoding auxiliary patch-info information for each of the partitions. 18 . The method according to claim 12 , wherein the information on the partition contains information indicating whether partitioning is applied to the point cloud. 19 . The method according to claim 18 , wherein the information on the partition contains 3D bounding box information, 2D bounding box information, or both. 20 . A computer-readable non-transitory recording medium storing image data received, decoded, and used by a scalable point cloud decoding apparatus in a process of reconstructing an image, wherein the image data includes an encoded texture image, an encoded geometry image, encoded occupancy map information, and encoded auxiliary patch-info information, the encoded texture image is used to acquire a decoded texture image for each partition, at least one item selected from among the encoded geometry image, the encoded occupancy map information, and the encoded auxiliary patch-info information is used to reconstruct a geometry image, and the texture image for each partition and the geometry image are used to reconstruct a point cloud.
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