Abstract: Methods and apparatuses of encoding a video stream using video point cloud coding include obtaining a source point cloud; generating a geometry map and a texture map based on the source point cloud; generating a reconstructed geometry map and a reconstructed texture map using lossy coding without using recoloring, wherein a resolution of the reconstructed geometry map is same as a resolution of the reconstructed texture map; obtaining a point of the source point cloud corresponding to a geometry pixel of the geometry map and a texture pixel of the texture map; selecting a color of the texture pixel based on a color of the obtained point; and generating an encoded video stream based on the selected color, the geometry map, and the texture map.

Abstract: A method for 3D human model reconstruction and animation includes receiving a two-dimensional (2D) image of a human, segmenting the 2D image into a foreground with the human and a background without the human in the 2D image, generating a parametric model comprising a pose, a shape, and one or more rigging parameters based on the human in the foreground, predicting a textured three-dimensional (3D) model using implicit surface reconstruction of the human in the foreground, aligning the parametric model and the textured 3D model using a 3D registration, and generating a textured 3D clothed human model based on the aligned parametric model and the predicted textured 3D model.

Abstract: A plurality of two-dimensional (2D) images of the scene is received. Geometric information and semantic information of each of the plurality of 2D images is determined. The geometric information indicates a detected line and a reference direction in the respective 2D image. The semantic information includes classification information of pixels in the respective 2D image. A layout estimation associated with the respective 2D image of the scene is determined based on the geometric information and the semantic information of the respective 2D image. A combined layout estimation associated with the scene is determined based on a plurality of the determined layout estimations associated with the plurality of 2D images of the scene. The Manhattan layout associated with the scene is generated based on the combined layout estimation. The Manhattan layout includes at least a three-dimensional (3D) shape of the scene that includes wall faces orthogonal with respect to each other.

Abstract: Aspects of the disclosure include methods, apparatuses, and non-transitory computer-readable storage mediums for generating a three-dimensional (3D) geometry of a room from a panorama image of the room. An apparatus includes processing circuitry that determine two-dimensional (2D) positions of wall corner points of the room in the panorama image based on a user input. Each wall corner point is in one of a floor plane or a ceiling plane of the room. The processing circuitry calculates 3D positions of the wall corner points based on the 2D positions of the wall corner points, a size of the panorama image, and a distance between the floor plane and a capture position of a device capturing the panorama image, determines a room layout based on an order of the wall corner points, and generates the 3D geometry based on the room layout and the 3D positions of the wall corner points.

Abstract: Aspects of the disclosure include methods, apparatuses, and non-transitory computer-readable storage mediums for generating a floor plan from a point cloud model. An apparatus includes processing circuitry that receives an input three-dimensional point cloud corresponding to a three-dimensional space. The processing circuitry determines a plurality of wall planes in the received input three-dimensional point cloud. The processing circuitry generates a plurality of line segments. Each line segment is generated by projecting a respective wall plane of the plurality of wall planes to a floor plane in the three-dimensional space. The processing circuitry represents the plurality of wall planes in the three-dimensional space using the plurality of line segments in a two-dimensional space corresponding to the floor plan. The processing circuitry adjusts the plurality of line segments in the two-dimensional space to improve the floor plan.

Abstract: Methods and apparatuses of encoding a video stream using video point cloud coding include obtaining a source point cloud; obtaining a geometry-reconstructed point cloud, wherein the geometry-reconstructed point cloud is reconstructed using lossy coding; obtaining a target point included in the geometry-reconstructed point cloud; performing at least one of a forward K-dimensional (KD)-tree search to determine a first plurality of points of the source point cloud which are nearest neighbors to the target point, and a backward KD-tree search to determine a second plurality of points of the source point cloud for which the target point is a nearest neighbor; determining an average color value based on at least one of a first average color value of the first plurality of points and a second average color value of the second plurality of points; selecting a color value for the target point based on the average color value; and generating an encoded video stream based on the selected color value.

Abstract: Methods and apparatuses of encoding a video stream using video point cloud coding include obtaining a source point cloud; generating a geometry map and a texture map based on the source point cloud; generating a reconstructed geometry map and a reconstructed texture map using lossy coding without using recoloring, wherein a resolution of the reconstructed geometry map is same as a resolution of the reconstructed texture map; obtaining a point of the source point cloud corresponding to a geometry pixel of the geometry map and a texture pixel of the texture map; selecting a color of the texture pixel based on a color of the obtained point; and generating an encoded video stream based on the selected color, the geometry map, and the texture map.

Abstract: Methods and apparatuses of encoding a video stream encoded using video point cloud coding include obtaining a source point cloud; generating an occupancy map including one or more pixels based on the source point cloud, an occupancy value associated with each pixel being a non-binary value; encoding the occupancy map to generate an encoded occupancy map, wherein a block of the encoded occupancy map corresponds to the one or more pixels of the occupancy map; selecting an occupancy value of the block based on the one or more pixels; and generating an encoded video stream based on the selected occupancy value.

Abstract: Aspects of the disclosure include methods, apparatuses, and non-transitory computer-readable storage mediums for generating a floor plan from a point cloud model. An apparatus includes processing circuitry that receives an input three-dimensional point cloud corresponding to a three-dimensional space. The processing circuitry determines a plurality of wall planes in the received input three-dimensional point cloud. The processing circuitry generates a plurality of line segments. Each line segment is generated by projecting a respective wall plane of the plurality of wall planes to a floor plane in the three-dimensional space. The processing circuitry represents the plurality of wall planes in the three-dimensional space using the plurality of line segments in a two-dimensional space corresponding to the floor plan. The processing circuitry adjusts the plurality of line segments in the two-dimensional space to improve the floor plan.

Abstract: Aspects of the disclosure include methods, apparatuses, and non-transitory computer-readable storage mediums for generating a three-dimensional (3D) geometry of a room from a panorama image of the room. An apparatus includes processing circuitry that determine two-dimensional (2D) positions of wall corner points of the room in the panorama image based on a user input. Each wall corner point is in one of a floor plane or a ceiling plane of the room. The processing circuitry calculates 3D positions of the wall corner points based on the 2D positions of the wall corner points, a size of the panorama image, and a distance between the floor plane and a capture position of a device capturing the panorama image, determines a room layout based on an order of the wall corner points, and generates the 3D geometry based on the room layout and the 3D positions of the wall corner points.

Abstract: A method, computer program, and computer system is provided for 3D pose graph reconstruction. 3D reconstruction of indoor buildings for VR/AR applications, such as virtual touring, digital museum, and virtual home sale, may be performed based on estimating pose graph and transformation matrix between cameras by recognizing markers on the ground in panorama images. Image data corresponding to one or more views of a first camera is received. One or more markers corresponding to a second camera are identified within the received image data. A pose graph corresponding to the one or more views of the first camera is constructed based on the identified one or more markers, the pose graph comprising at least an edge.

Abstract: Described herein is a technology for facilitating classification of an object. In one implementation, at least one quotient appearance manifold mapping is constructed from a sample image to untangle appearance fiber bundles. A feature characteristic of the sample image may then be extracted based on the quotient appearance manifold mapping. A classifier may further be trained based on the extracted feature, and adapted for associating the object with an object class.

Abstract: A control system and method generate torque comments for motion of a target system in response to observations of a source system. Constraints and balance control may be provided for more accurate representation of the motion as replicated by the target system.

Abstract: Described herein is a technology for facilitating coordinated description in image analysis. In one implementation, the technology includes receiving image data including at least first and second descriptors (204) describing portions of the image data. The first and second descriptors are coordinated by determining at least one conditional probability of observing the first descriptor in the image data given an occurrence of the second descriptor (206). A classifier may then be trained based on the conditional probability (208).

Abstract: Described herein is a method and system for facilitating automatic classification of regions-of-interest (ROIs). Contrast enhanced image data may be received (202) and processed to generate at least one texture value of at least one ROI in the image data (204). The ROI may be automatically classified as either a mass or a non-mass like enhancement (NMLE) based on the texture value (e.g., bumpiness) (208).

Abstract: A fan includes a bracket, a stator, a rotor, and a slanting portion. The bracket includes a tray, and a frame circling the tray. The stator is mounted to and circled by the frame. The rotor includes a shaft rotatably mounted to the stator, and a shell coupled to the shaft. The shell covers the stator, and the shell and the tray of the bracket cooperatively enclose the stator. An assembly clearance is formed between a bottom end of the shell and a top surface of the tray. The slanting portion circles the tray and extends down from the bottom end of the shell, slanting away and spaced from the tray.

Abstract: A method for performing pharmacokinetic analysis in magnetic resonance (MR) images includes administering a dose of contrast agent (CA) into a subject. A sequence of medical images is acquired of the subject at set temporal intervals. The time-based behavior of concentrations of CA is described within the subject for each voxel of each medical image of the sequence of medical images based on a reference voxel using a compartmental model for pharmacokinetic analysis that is based on a set of compartmental model parameters. The compartmental model is solved for each of the compartmental model parameters. The solution for the compartmental model parameters is used to estimate one or more parameters of physiological significance.

Abstract: A technology for facilitating computer-aided detection (CAD) includes in one implementation, receiving an enhancement pattern (602) generated from image data. The enhancement pattern is pre-processed to produce an alert level (604, 606, 608). Computationally-intensive analysis may be performed on a region of interest if it corresponds to an enhancement pattern with a high alert level.

Abstract: A method and system for facilitating computer-aided detection (CAD) in which, in one implementation, image data is received (302) and iterations of an iterative segmentation process is performed on the image data. Each iterative segmentation process may include ascertaining whether a segment is normal (304), removing the segment from the image if ascertained to be normal (308) and transforming the shape of the segment (310). The iterative segmentation process may be stopped if a stop condition is met (312).

Abstract: A fan includes a bracket, a stator, a rotor, and a slanting portion. The bracket includes a tray, and a frame circling the tray. The stator is mounted to and circled by the frame. The rotor includes a shaft rotatably mounted to the stator, and a shell coupled to the shaft. The shell covers the stator, and the shell and the tray of the bracket cooperatively enclose the stator. An assembly clearance is formed between a bottom end of the shell and a top surface of the tray. The slanting portion circles the tray and extends down from the bottom end of the shell, slanting away and spaced from the tray.