Abstract: An apparatus includes a generation unit configured to generate map information including a position of a feature point and identification information on an index in an image of a real space captured by a capturing apparatus, a collation unit configured to collate the identification information on the index in the generated map information with the identification information on the index in one or more pieces of registered map information, and to extract map information from the one or more pieces of registered map information based on a result of the collation, and an estimation unit configured to estimate a position and orientation of the capturing apparatus based on the position of the feature point in the extracted map information and the position of the feature point in the generated map information.

Abstract: An image decoding method according to the present document comprises the steps of: deriving flag information indicating whether valid coefficients are present in a second area excluding a first area of the upper left corner of the current block; parsing an MTS index from a bitstream on the basis of the flag information indicating the absence of valid coefficients in the second area; and deriving residual samples for the current block by applying a conversion kernel derived on the basis of the MTS index to conversion coefficients of the first area, wherein the flag information may be derived by determining, for each scan sub-block in which the valid coefficients are scanned, whether the valid coefficients are present in the second area.

Abstract: Methods, systems, apparatus for video processing are described. The processing may include encoding, decoding or transcoding. One example video processing method includes performing a conversion between a video and a bitstream of the video according to a rule, and wherein the rule specifies that a syntax element is included in a profile, tier, level information syntax structure to indicate whether one or more general constraint information syntax elements are included in a general constraint information syntax structure and/or whether the general constraint information syntax structure is included in the profile, tier, level information syntax structure.

Abstract: There is provided a control device including an image display unit configured to acquire, from a flying body, an image captured by an imaging device provided in the flying body and to display the image, and a flight instruction generation unit configured to generate a flight instruction for the flying body based on content of an operation performed with respect to the image captured by the imaging device and displayed by the image display unit.

Abstract: An image decoding device, includes a filter unit using, as an input, a decoded signal prior to the filtering process and output a filtered decoded signal. The filter unit performs clipping processing on the decoded signal prior to the filtering process such that the absolute value of a differential value between a reference pixel value and a pixel value of the decoded signal prior to the filtering process is less than or equal to a predefined threshold value, and to generate the filtered decoded signal through the linear weighted addition of the value after the clipping processing is performed and the pixel value of the decoded signal prior to the filtering process; and a large-small relationship between the threshold value for a luma signal and the threshold value for a chroma signal are defined such that the large-small relationship is unchanged when an internal bit depth is changed.

Abstract: In various embodiments, a tunable VMAF application reduces an amount of influence that image enhancement operations have on perceptual video quality estimates. In operation, the tunable VMAF application computes a first value for a first visual quality metric based on reconstructed video content and a first enhancement gain limit. The tunable VMAF application computes a second value for a second visual quality metric based on the reconstructed video content and a second enhancement gain limit. Subsequently, the tunable VMAF application generates a feature value vector based on the first value for the first visual quality metric and the second value for the second visual quality metric. The tunable VMAF application executes a VMAF model based on the feature value vector to generate a tuned VMAF score that accounts, at least in part, for at least one image enhancement operation used to generate the reconstructed video content.

Abstract: A system for optical measurement of an object includes a radiation generating device, a capturing device, and an evaluation device. The radiation generating device is configured to emit electromagnetic radiation onto the object. The capturing device includes an image sensor. The capturing device is configured to capture a measurement image as a result of an exposure of the image sensor with radiation returned from the object. The capturing device is configured to vary a focus setting (D) during the exposure. The evaluation device is configured to determine coordinates of at least one location on the object based on the captured measurement image.

Abstract: A method of video processing includes performing a conversion between a video and a bitstream of the video according to a rule, wherein the rule specifies that a sub-bitstream extraction process is implemented to generate a sub-bitstream for decoding, wherein the sub-bitstream extraction process is configured to extract, from the bitstream, a sub-bitstream with a target highest temporal identifier, and wherein, the rule specifies that, during the extracting, upon removing a video coding layer (VCL) network abstraction layer (NAL) unit, filler data units and filler supplemental enhancement information (SEI) messages in SEI NAL units that are associated with the VCL NAL unit are also removed.

Abstract: The disclosure provides an eye tracking method and an eye tracking device. The method includes obtaining a reference interpupillary distance value; taking images of a user of a 3D display, and finding a first eye pixel coordinate corresponding to a first eye of the user and a second eye pixel coordinate corresponding to a second eye of the user in each image; detecting a first and a second eye spatial coordinates of the first and the second eyes, and determining projection coordinates based on the first eye spatial coordinate, the second eye spatial coordinate, and optical parameters of image capturing elements; determining an optimization condition related to the first and second eye spatial coordinates based on the first and second eye pixel coordinates, the projection coordinates, and the reference interpupillary distance value of each image; and optimizing the first and second eye spatial coordinates based on the optimization condition.

Abstract: A position and pose determination unit (103) is configured to determine a position and an pose of the video acquisition unit (110) in such a way that a level of hiding caused by overlapping of objects becomes low based on environmental object information indicating an environmental object including a structural object present in the monitored area and a placed object placed in the structural object, and staying characteristic information indicating a staying characteristic of the object determined depending on the environmental object. The analysis and display unit (111) is configured to perform at least one of analyzing a video captured by the video acquisition unit (103) at the position and the pose determined by the position and pose determination unit (110) and displaying the video.

Abstract: An image processing method includes obtaining statistics information of a block of an image frame, determining whether the statistics information satisfies a condition, and disabling cross-component filtering (CCF) for the block in response to the statistics information satisfying the condition.

Abstract: A video coding mechanism is disclosed. The mechanism includes receiving a bitstream comprising a slice and a luma mapping with chroma scaling (LMCS) adaptation parameter set (APS) including LMCS parameters. The mechanism further includes determining that the LMCS APS is referenced in data related to the slice. The mechanism further includes decoding the slice using LMCS parameters from the LMCS APS based on the reference to the LMCS APS. The mechanism further includes forwarding the slice for display as part of a decoded video sequence.

Abstract: An encoder includes circuitry and memory. Using the memory, the circuitry performs prediction on an image. A motion vector predictor list used in the prediction includes a spatially neighboring motion vector predictor obtained from a block spatially neighboring a current block, and a spatially broad motion vector predictor obtained from a block positioned at any of a plurality of predetermined positions in a second range that is broader than a first range that spatially neighbors the current block. The plurality of predetermined positions are defined by a regular interval using the top-left of a current picture as a reference point.

Abstract: A method of decoding an encoded video. The method includes obtaining the encoded video bitstream and determining whether a chroma array type of a video sequence included in the encoded video bitstream is a first chroma array type indicating that the video sequence includes multiple color planes and that the multiple color planes are jointly. In addition, based on determining that the chroma array type is not the first chroma array type, the method further includes setting a value of at least one syntax element to zero without parsing the at least one syntax element from the encoded video bitstream, and based on the value of the at least one syntax element being zero, decoding the video sequence without applying at least one tool corresponding to the at least one syntax element.

Abstract: Coding techniques for 360-degree video are described. An encoder selects a projection format and maps the 360-degree video to a 2D planar video using the selected projection format. The encoder encodes the 2D planar video in a bitstream and further signals, in the bitstream, parameters identifying the projection format. The parameters identifying the projection format may be signaled in a video parameter set, sequence parameter set, and/or picture parameter set of the bitstream. Different projection formats that may be signaled include formats using geometries such as equirectangular, cubemap, equal-area, octahedron, icosahedron, cylinder, and user-specified polygon. Other parameters that may be signaled include different arrangements of geometric faces or different encoding quality for different faces. Corresponding decoders are also described. In some embodiments, projection parameters may further include relative geometry rotation parameters that define an orientation of the projection geometry.

Abstract: According to one embodiment, disclosed is a method by which a camera module capable of acquiring depth information controls the output time point and the reception time point of light. By controlling both the output time point and the reception time point of light, the camera module can acquire the light of phases in which adjacent reception pixels differ from one another despite controlling light sources or reception pixels in line units.

Abstract: An image encoding/decoding method and apparatus of the present invention may divide one picture into a plurality of division units, determine whether to perform filtering on a boundary of a current division unit based on a predetermined flag, and perform filtering on the boundary of the current division unit in response to the determination.

Abstract: In various embodiments, an encoder comparison application compares the performance of different configured encoders. In operation, the encoder comparison application generates a first global convex hull of video encode points based on a first configured encoder and a set of subsequences included in a source video sequence. Each video encode point is associated with a different encoded version of the source video sequence. The encoder comparison application also generates a second global convex hull of video encode points based on a second configured encoder and the subsequences. Subsequently, the encoder configuration application computes a performance value for an encoding comparison metric based on the first global convex hull and the second global convex hull. Notably, the first performance value estimates a difference in performance between the first configured encoder and the second configured encoder.

Abstract: A positioning system and a calibration method of an objection location are provided. The calibration method includes the following. Roadside location information of a roadside unit (RSU) is obtained. Object location information of one or more objects is obtained. The object location information is based on a satellite positioning system. An image identification result of the object or the RSU is determined according to images of one or more image capturing devices. The object location information of the object is calibrated according to the roadside location information and the image identification result. Accordingly, the accuracy of the location estimation may be improved.

Abstract: Automated object identification and tracking systems and methods may include an imaging device operatively coupled to a movable base. The movable base may include one or more actuators to adjust pan and/or tilt orientations of the movable base and imaging device, and the imaging device may include a zoom controller to adjust a zoom level of the imaging device. A controller of the movable base may receive imaging data from the imaging device, process the imaging data to identify an object, and track the object over a plurality of frames of imaging data by instructing adjustments to a pan orientation, a tilt orientation, and/or a zoom level to substantially maintain the identified object at a desired size and within a field of view of the imaging device based on a position and/or size of the object represented within the imaging data.