Abstract: To compute an image of a dynamic 3D scene comprising a 3D object, a description of a deformation of the 3D object is received, the description comprising a cage of primitive 3D elements and associated animation data from a physics engine or an articulated object model. For a pixel of the image the method computes a ray from a virtual camera through the pixel into the cage animated according to the animation data and computes a plurality of samples on the ray. Each sample is a 3D position and view direction in one of the 3D elements. The method computes a transformation of the samples into a canonical cage. For each transformed sample, the method queries a learnt radiance field parameterization of the 3D scene to obtain a color value and an opacity value. A volume rendering method is applied to the color and opacity values producing a pixel value of the image.

Abstract: A neural optimizer is disclosed that is easily applicable to different fitting problems, can run at interactive rates without requiring significant efforts, does not require hand crafted priors, carries over information about previous iterations of the solve, controls the learning rate of each parameter independently for robustness and convergence speed, and combines updates from gradient descent and from a method capable of very quickly reducing the fitting energy. A neural fitter estimates the values of the parameters ? by iteratively updating an initial estimate ?0.

Abstract: The techniques described herein disclose a system that is configured to detect and track the three-dimensional pose of an object (e.g., a head-mounted display device) in a color image using an accessible three-dimensional model of the object. The system uses the three-dimensional pose of the object to repair pixel depth values associated with a region (e.g., a surface) of the object that is composed of material that absorbs light emitted by a time-of-flight depth sensor to determine depth. Consequently, a color-depth image (e.g., a Red-Green-Blue-Depth image or RGB-D image) can be produced that does not include dark holes on and around the region of the object that is composed of material that absorbs light emitted by the time-of-flight depth sensor.

Abstract: Keypoints are predicted in an image. A neural network is executed that is configured to predict each of the keypoints as a 2D random variable, normally distributed with a 2D position and 2×2 covariance matrix. The neural network is trained to maximize a log-likelihood that samples from each of the predicted keypoints equal a ground truth. The trained neural network is used to predict keypoints of an image without generating a heatmap.

Abstract: Keypoints are predicted in an image. Predictions are generated for each of the keypoints of an image as a 2D random variable, normally distributed with location (x, y) and standard deviation sigma. A neural network is trained to maximize a log-likelihood that samples from each of the predicted keypoints equal a ground truth. The trained neural network is used to predict keypoints of an image without generating a heatmap.

Abstract: In various examples there is an apparatus for aligning three-dimensional, 3D, representations of people. The apparatus comprises at least one processor and a memory storing instructions that, when executed by the at least one processor, perform a method comprising accessing a first 3D representation which is an instance of a parametric model of a person; accessing a second 3D representation which is a photoreal representation of the person; computing an alignment of the first and second 3D representations; and computing and storing a hologram from the aligned first and second 3D representations such that the hologram depicts parts of the person which are observed in only one of the first and second 3D representations; or controlling an avatar representing the person where the avatar depicts parts of the person which are observed in only one of the first and second 3D representations.

Abstract: In various examples there is an apparatus for aligning three-dimensional, 3D, representations of people. The apparatus comprises at least one processor and a memory storing instructions that, when executed by the at least one processor, perform a method comprising accessing a first 3D representation which is an instance of a parametric model of a person; accessing a second 3D representation which is a photoreal representation of the person; computing an alignment of the first and second 3D representations; and computing and storing a hologram from the aligned first and second 3D representations such that the hologram depicts parts of the person which are observed in only one of the first and second 3D representations; or controlling an avatar representing the person where the avatar depicts parts of the person which are observed in only one of the first and second 3D representations.

Abstract: The invention provides a fluorinated chitosan derivative as a drug carrier, which has the following structure: a fluorine-containing compound covalently attached to the backbone of chitosan. The chitosan has a molecular weight in the range of 1000-5000000, a degree of deacetylation of not less than 55%, and a viscosity in the range of 25-1000 cps. The fluorine-containing compound is a fluorine-containing aliphatic chain shown by the following chemical formula (I) or an aromatic ring with functional groups shown by the following formula (II) wherein R1 is halogen (fluorine, chlorine, bromine, iodine), or a halogen-substituted alkane, cycloalkane, aldehyde group, carboxyl group, alkenyl group, alkynyl group, hydroxyl group, sulfonyl chloride, sulfonic acid bond or mercapto group, for interacting with a primary amino group. The compounds of the present invention can be universally bound to a variety of drugs to promote drug absorption and bioavailability, and reduce toxicity.

Abstract: An ordering method and an ordering system supporting integration of coupon cancellation after verification are disclosed in this application, wherein the method includes: receiving an ordering request initiated by a user for a store; retrieving coupon information of at least one coupon received by the user from the store, wherein the coupon information contains at least one product identifier and product deduction information; adding at least one product corresponding to the coupon information to a to-be-paid product list, determining a to-be-paid amount for products in the to-be-paid product list according to the product deduction information; in response to receiving a payment request initiated by the user, completing payment and coupon cancellation after verification according to the to-be-paid amount for products in the to-be-paid product list.

Abstract: An aerosol generating product includes an aerosol atomizing element and a smoke cooling element, and the smoke cooling element is located downstream of the flow direction of the smoke generated by the aerosol atomizing element. A filter element is located downstream of the flow direction of the smoke through which the smoke cooling element passes; or a hollow element located upstream of the flow direction of the smoke through which the smoke cooling element passes. The smoke cooling element is composed of particles, and the structure includes a gap for smoke of a cigarette to pass through. The gap through which cigarette smoke can pass is a three-dimensional and non-linear gap. The structure is in the form of rods. When the smoke aerosol passes through the cooling element, ensuring the smoke to pass through smoothly.

Abstract: A tracker is described which comprises a processor configured to receive captured sensor data depicting an object. The processor is configured to access a rigged polygon mesh model of the object and to compute a plurality of approximate surface normals of a limit surface of the rigged polygon mesh. The processor is configured to compute values of pose parameters of the model by calculating an optimization to fit the model to the captured sensor data where the optimization uses an evaluation function based on the plurality of approximate surface normals.

Abstract: A built-in electrode electrical capacitance tomography sensor, characterized in that the electrical capacitance tomography sensor is a barrel sensor, and sequentially comprises, from inside to outside, an array distribution electrode (1), an electrode insulating sleeve (2), a flange outer tube (3), an insulating tube (4) and a signal transmission line. The array distribution electrode (1) includes N electrode sheets of the same size and consists of measurement ends and fixed ends, N being an integer of 8-16. The electrode is connected to an electrical capacitance tomography signal acquisition system (13) by means of a transmission line, and the acquired electrical capacitance data is sent to the electrical capacitance tomography signal acquisition system (13) by means of a signal transmission line, and is then sent to an imaging computer by means of the electrical capacitance tomography signal acquisition system (13) so as to complete image reconstruction.

Abstract: In various examples there is an apparatus for detecting position and orientation of an object. The apparatus comprises a memory storing at least one frame of captured sensor data depicting the object. The apparatus also comprises a trained machine learning system configured to receive the frame of the sensor data and to compute a plurality of two dimensional positions in the frame. Each predicted two dimensional position is a position of sensor data in the frame depicting a keypoint, where a keypoint is a pre-specified 3D position relative to the object. At least one of the keypoints is a floating keypoint depicting a pre-specified position relative to the object, lying inside or outside the object's surface. The apparatus comprises a pose detector which computes the three dimensional position and orientation of the object using the predicted two dimensional positions and outputs the computed three dimensional position and orientation.

Abstract: A built-in electrode electrical capacitance tomography sensor, characterized in that the electrical capacitance tomography sensor is a barrel sensor, and sequentially comprises, from inside to outside, an array distribution electrode (1), an electrode insulating sleeve (2), a flange outer tube (3), an insulating tube (4) and a signal transmission line. The array distribution electrode (1) includes N electrode sheets of the same size and consists of measurement ends and fixed ends, N being an integer of 8-16. The electrode is connected to an electrical capacitance tomography signal acquisition system (13) by means of a transmission line, and the acquired electrical capacitance data is sent to the electrical capacitance tomography signal acquisition system (13) by means of a signal transmission line, and is then sent to an imaging computer by means of the electrical capacitance tomography signal acquisition system (13) so as to complete image reconstruction.

Abstract: A method and an apparatus for presenting and issuing a coupon based on an internet platform. The presenting method includes: presenting a prompt information on issuing a coupon package, where the coupon package contains two or more sub-coupons; receiving a confirmation-collecting operation corresponding to the coupon package; sending a coupon-package issuing request for the coupon package based on the confirmation-collecting operation; and upon receiving a confirmation information on the coupon-package issuing request, displaying issue information on the coupon package; the sub-coupons contained in the coupon package is listed in the issue information on the coupon package.

Abstract: A tracker is described which comprises a processor configured to receive captured sensor data depicting an object. The processor is configured to access a rigged polygon mesh model of the object and to compute a plurality of approximate surface normals of a limit surface of the rigged polygon mesh. The processor is configured to compute values of pose parameters of the model by calculating an optimization to fit the model to the captured sensor data where the optimization uses an evaluation function based on the plurality of approximate surface normals.

Abstract: In various examples there is an apparatus for detecting position and orientation of an object. The apparatus comprises a memory storing at least one frame of captured sensor data depicting the object. The apparatus also comprises a trained machine learning system configured to receive the frame of the sensor data and to compute a plurality of two dimensional positions in the frame. Each predicted two dimensional position is a position of sensor data in the frame depicting a keypoint, where a keypoint is a pre-specified 3D position relative to the object. At least one of the keypoints is a floating keypoint depicting a pre-specified position relative to the object, lying inside or outside the object's surface. The apparatus comprises a pose detector which computes the three dimensional position and orientation of the object using the predicted two dimensional positions and outputs the computed three dimensional position and orientation.

Abstract: A tracker is described which comprises a processor configured to receive captured sensor data depicting an object. The processor is configured to access a rigged polygon mesh model of the object and to compute a plurality of approximate surface normals of a limit surface of the rigged polygon mesh. The processor is configured to compute values of pose parameters of the model by calculating an optimization to fit the model to the captured sensor data where the optimization uses an evaluation function based on the plurality of approximate surface normals.

Abstract: A tracker is described which comprises a processor configured to receive captured sensor data depicting an object. The processor is configured to access a rigged polygon mesh model of the object and to compute a plurality of approximate surface normals of a limit surface of the rigged polygon mesh. The processor is configured to compute values of pose parameters of the model by calculating an optimization to fit the model to the captured sensor data where the optimization uses an evaluation function based on the plurality of approximate surface normals.

Abstract: Methods and devices for obtaining search results. For example, a method may include receiving, by a computing device, search information input by a current user and a target user that is associated with the search information and designated by the current user. The computing device may transmit to a server terminal a search request including the search information and the target user such that the server terminal may obtain feature information of the target user based on the search information of the search request, obtain a search result corresponding to the feature information based on the search information, and return the search result to the client terminal, which may receive and display the search result. The implementations provide an approach for obtaining search results associated with a desired target user.