Abstract: The present application discloses a recombinant Newcastle disease virus genome, a recombinant Newcastle disease virus rNDV-VEGF-Trap containing the genome and a preparation method therefor, a DNA molecule encoding the recombinant Newcastle disease virus genome, and a use of the genome and the recombinant Newcastle disease virus in the preparation of a drug for treating cancer. The recombinant Newcastle disease virus provided by the present application relates to inserting a coding gene of VEGF-Trap into the genome of the recombinant Newcastle disease virus, such that the recombinant Newcastle disease virus obtained therefrom is replicated with a strong replication capability, thereby killing host cancer cells; moreover, the recombinant Newcastle disease virus has reliable safety for non-cancer cells, and shows improved anti-tumor effect and oncolytic efficiency.

Abstract: A method for correcting interference fringes includes: obtaining correction parameter sets of different photographing distances; obtaining a to-be-corrected image and calculating an average depth value of the to-be-corrected image; selecting a target correction parameter set corresponding to the average depth value from the correction parameter sets of different photographing distances; and correcting first pixel values of to-be-corrected pixels at the different coordinate positions in the to-be-corrected image according to different target correction parameters corresponding to the different coordinate positions in the target correction parameter set, to obtain a corrected image. Each of the correction parameter sets includes different correction parameters corresponding to different coordinate positions. The average depth value includes an average value of depth values corresponding to a plurality of to-be-corrected pixels in the to-be-corrected image.

Abstract: A method for correcting interference fringes includes: obtaining interference fringe images with different photographing distances; obtaining a to-be-corrected image including to-be-corrected pixels, and calculating a depth value of each to-be-corrected pixel in the to-be-corrected image; selecting, from the interference fringe images with different photographing distances, an interference fringe image corresponding to the depth value of each to-be-corrected pixel as a target interference fringe image; extracting first pixel values of target coordinate positions in the target interference fringe image; and correcting second pixel values of to-be-corrected pixels according to the first pixel values corresponding to the to-be-corrected pixels to obtain a corrected image.

Abstract: A method for search of light spot positions, includes the following steps: calibrating spatial template distribution of light spots in an object space of a distance measurement system and spatial emission angle factors of the light spots; calculating coordinates of offset light spots on a pixel unit of a collector after impact deformation occurs in the distance measurement system, and obtaining serial numbers of the offset light spots; and according to the coordinates of the offset light spots on the pixel unit of the collector and the serial numbers, calibrating the distance measurement system after the impact deformation occurs to obtain new spatial emission angle factors, and completing the search of light spot positions.

Abstract: A depth image engine and a depth image calculation method are provided. The depth image engine comprises: a buffer, configured to receive a data flow of a first image; an image rotator, configured to perform, after the buffer receives the entire data flow of the first image, a rotation operation on the first image to generate a second image; and a depth value calculator, configured to receive the second image and a reference image to perform a matching calculation on the second image and the reference image to generate a depth image.

Abstract: A depth calculation processor includes: an input port, configured to receive image data from an image sensor; a demultiplexer, connected to the input port, and configured to demultiplex the image data from the input port and output first image data into a first line and second image data into a second line; a grayscale image engine, configured to process the first image data from the first line to generate processed first image data; a depth image engine, configured to receive the second image data from the second line, and calculate depth image data based on the second image data; a multiplexer, configured to output the processed first image data from the grayscale image engine and the depth image data from the depth image engine; and an output port, configured to output the processed first image data and the depth image data from the multiplexer.

Abstract: A depth calculation processor, a data processing method, and a 3D image device are disclosed herein. The depth calculation processor includes: at least two input ports configured to receive a first image data, wherein the first image data comprises at least a structured light image acquired under projection of a structured light; a data processing engine configured to perform a calculation process on the first image data to output a second image data, wherein the second image data comprises at least a depth map, wherein the data processing engine comprises at least a depth processing engine configured to perform a depth calculation process on the structured light image to obtain the depth map; and at least an output port coupled to the data processing engine and configured to output the second image data to a host device.

Abstract: A depth calculation processor includes: an input port, configured to receive image data from an image sensor; a demultiplexer, connected to the input port, and configured to demultiplex the image data from the input port and output first image data into a first line and second image data into a second line; a grayscale image engine, configured to process the first image data from the first line to generate processed first image data; a depth image engine, configured to receive the second image data from the second line, and calculate depth image data based on the second image data; a multiplexer, configured to output the processed first image data from the grayscale image engine and the depth image data from the depth image engine; and an output port, configured to output the processed first image data and the depth image data from the multiplexer.

Abstract: A depth calculation processor comprises: an input port, configured to receive image data from an image sensor; a demultiplexer, connected to the input port, and configured to demultiplex the image data from the input port and output first image data into a first line and second image data into a second line; a grayscale image engine, configured to process the first image data from the first line to generate processed first image data; a depth image engine, configured to receive the second image data from the second line, and calculate depth image data based on the second image data; a multiplexer, configured to output the processed first image data from the grayscale image engine and the depth image data from the depth image engine; and an output port, configured to output the processed first image data and the depth image data from the multiplexer.

Abstract: The specification provides a depth imaging method and device and a computer-readable storage medium. The method includes: controlling an emission module comprising a light emitting device to emit at least two speckle patterns that change temporally to a target object; controlling an acquisition module comprising a light sensor to acquire reflected speckle patterns of the at least two speckle patterns reflected by the target object; and performing spatial-temporal stereo matching by using the reflected speckle patterns and the at least two reference speckle patterns, to calculate offsets of pixel points between speckles of the at least two reference speckle patterns and speckles of the reflected speckle patterns, and calculating depth values of the pixel points according to the offsets.

Abstract: The present disclosure provides a structured light projection module comprising: a Vertical-Cavity Surface-Emitting Laser (VCSEL) array light source that includes a semiconductor substrate and at least two VCSEL sub-arrays arranged thereon. The at least two VCSEL sub-arrays include VCSEL light sources. The structured light projection module further includes a diffractive optical element (DOE) that includes at least two DOE sub-units. The DOE sub-units are respectively corresponding to the VCSEL sub-arrays and configured to project multiple copies of light beams emitted by the corresponding at least two VCSEL sub-arrays.

Abstract: The present application provides an identity authentication method and an apparatus. The method may include obtaining a sequence of depth images containing a target face and a sequence of original two-dimensional (2D) images containing the target face, and performing identity authentication. The identity authentication may be conducted by: calculating a target face three-dimensional (3D) texture image according to the depth images containing the target face and the original 2D images containing the target face; projecting the target face 3D texture image to a 2D plane to obtain a target face 2D image; extracting feature information from the target face 2D image; comparing the feature information of the target face 2D image with feature information of a reference face 2D image to determine a similarity value; and in response to that the similarity value exceeds a first threshold, determining that the identity authentication succeeds.

Abstract: A depth calculation processor, a data processing method, and a 3D image device are disclosed herein. The depth calculation processor includes: at least two input ports configured to receive a first image data, wherein the first image data comprises at least a structured light image acquired under projection of a structured light; a data processing engine configured to perform a calculation process on the first image data to output a second image data, wherein the second image data comprises at least a depth map, wherein the data processing engine comprises at least a depth processing engine configured to perform a depth calculation process on the structured light image to obtain the depth map; and at least an output port coupled to the data processing engine and configured to output the second image data to a host device.

Abstract: A depth calculation processor, a data processing method, and a 3D image device are disclosed herein. The depth calculation processor includes: two input ports to receive a first image data, wherein the first image data comprises structured light image acquired under projection of structured light; an input switch connected to the input ports and to convey all or some of the first image data from the input ports; a data processing engine connected to the input switch and to process the first image data that is output through the input switch and to output a second image data, wherein the second image data comprises a depth map, wherein the data processing engine comprises a depth processing engine to process the structured light image to obtain the depth map; and one output port connected to the data processing engine and to output the second image data to a main device.

Abstract: The present disclosure provides a structured light projection module comprising: a Vertical-Cavity Surface-Emitting Laser (VCSEL) array light source that includes a semiconductor substrate and at least two VCSEL sub-arrays arranged thereon. The at least two VCSEL sub-arrays include VCSEL light sources. The structured light projection module further includes a diffractive optical element (DOE) that includes at least two DOE sub-units. The DOE sub-units are respectively corresponding to the VCSEL sub-arrays and configured to project multiple copies of light beams emitted by the corresponding at least two VCSEL sub-arrays.

Abstract: The present disclosure provides a structured light projection module comprising: a Vertical-Cavity Surface-Emitting Laser (VCSEL) array light source that includes a semiconductor substrate and at least two VCSEL sub-arrays arranged thereon. The at least two VCSEL sub-arrays include VCSEL light sources. The structured light projection module further includes a diffractive optical element (DOE) that includes at least two DOE sub-units. The DOE sub-units are respectively corresponding to the VCSEL sub-arrays and configured to project multiple copies of light beams emitted by the corresponding at least two VCSEL sub-arrays.

Abstract: A depth calculation processor comprises: an input port, configured to receive image data from an image sensor; a demultiplexer, connected to the input port, and configured to demultiplex the image data from the input port and output first image data into a first line and second image data into a second line; a grayscale image engine, configured to process the first image data from the first line to generate processed first image data; a depth image engine, configured to receive the second image data from the second line, and calculate depth image data based on the second image data; a multiplexer, configured to output the processed first image data from the grayscale image engine and the depth image data from the depth image engine; and an output port, configured to output the processed first image data and the depth image data from the multiplexer.

Abstract: A depth image engine and a depth image calculation method are provided. The depth image engine comprises: a buffer, configured to receive a data flow of a first image; an image rotator, configured to perform, after the buffer receives the entire data flow of the first image, a rotation operation on the first image to generate a second image; and a depth value calculator, configured to receive the second image and a reference image to perform a matching calculation on the second image and the reference image to generate a depth image.

Abstract: The present application provides an identity authentication method and an apparatus. The method may include obtaining a sequence of depth images containing a target face and a sequence of original two-dimensional (2D) images containing the target face, and performing identity authentication. The identity authentication may be conducted by: calculating a target face three-dimensional (3D) texture image according to the depth images containing the target face and the original 2D images containing the target face; projecting the target face 3D texture image to a 2D plane to obtain a target face 2D image; extracting feature information from the target face 2D image; comparing the feature information of the target face 2D image with feature information of a reference face 2D image to determine a similarity value; and in response to that the similarity value exceeds a first threshold, determining that the identity authentication succeeds.

Abstract: The present invention discloses a television virtual touch control method and system. The television virtual touch control method is used in a television having a depth camera and includes the following steps: acquiring a human body image having depth information by the depth camera in real time; presetting an area excluding a hand area in a human body area as a reference area; extracting the depth information of the reference area and the hand area from the human body image; defining a virtual touch surface between the depth camera and the reference area at a first predetermined distance D1 from the reference area; and determining whether the hand area touches or penetrates through the virtual touch surface according to the depth information of the hand area, the depth information of the reference area and the first predetermined distance D1. The present invention has the beneficial effects of improving touch sensitivity and enhancing user experience.