Abstract: The present disclosure relates to a video recording apparatus and a controlling method thereof. According to an embodiment of the present disclosure, a video recording apparatus may include a motion detection sensor, a controller, and an application processor. The motion detection sensor may sense motion of an external object outside of a vehicle. The controller may be activated if the motion detection sensor senses motion of the external object and may monitor the external object through the motion detection sensor during a predetermined time period. An image processor may be activated based on a monitoring result of the external object so as to perform a video recording function.

Abstract: There is included a method and apparatus comprising computer code configured to cause a processor or processors to perform acquiring an input bitstream comprising metadata and video data, decoding the video data, determining whether the metadata comprises at least one flag signaling at least one component of a picture size of at least one picture of the video data, and signaling, in a case where it is determined that the metadata comprises the at least one flag, a display device to display the at least one picture from the video data according to the at least one flag.

Abstract: A video decoding method includes, determining a center motion vector of a current block by using a base motion vector of the current block based on affine model-based inter-prediction being performed in the current block, determining a reference range of an area to be referred to, with respect to the current block, based on a size of the current block, based on a reference area having a size of the reference range with respect to a point in a reference picture of the current block, the point being indicated by a central motion vector of the current block, deviating from or including a boundary of the reference picture, changing the reference area by parallelly translating the reference area into a current picture, and determining prediction samples of sub-blocks of the current block in the changed reference area from the reference picture.

Abstract: At least a method and an apparatus are presented for efficiently encoding or decoding video. For example, an intra prediction of an image block using at least one neural network from a context comprising pixels surrounding the image block is determined and an information relative to a transform method to apply for decoding the image block is also determined. The transform method is adapted to the neural network intra prediction mode of the block to encode or decode. The information relative to the transform method is inferred from the at least one neural network used in intra prediction of the image block at the encoding and either signaled or also inferred at the decoding.

Abstract: A point cloud data transmission method according to embodiments can comprise the steps of: acquiring point cloud data; encoding geometry information included in the point cloud data; encoding attribute information included in the point cloud data; and transmitting the encoded geometry information and the encoded attribute information.

Abstract: It is provided a method of prediction coding of a current block, comprising: obtaining an intra prediction mode of a left neighbor block of the current block and an intra prediction mode of an above neighbor block of the current block; constructing a Most Probable Mode (MPM) list of intra prediction modes for the current block, the MPM list comprising at least 5 entries of intra prediction modes as follows: {ang, 2+((ang+61)%64), 2+((ang?1)%64), 2+((ang+60)%64), 2+((ang) %64)} when at least a first condition is fulfilled, where ang represents the intra prediction mode of the left neighbor block or the intra prediction mode of the above neighbor block.

Abstract: A system and a method for an object detection system for detecting one or more objects in an aquatic environment includes a first image capture device; a second image capture device; a position scanner; a controller in electronic communication with the first image capture device, the second image capture device and the position scanner, the controller configured to receive a 2D image of a scene including the one or more objects; receive or resolve a stereo image of the scene; receive position information of the one or more objects in the scene; determine a depth data of the one or more objects in the scene based on the position information; detect one or more objects in the scene based on the 2D image, the stereo image, and the depth data of the one or more objects.

Abstract: The present invention refers to a vehicle display system, which comprises: a bracket; at least one bracket support member wherein the bracket support member comprises a receiving cavity to retain the bracket; a display cover coupled to the at least one bracket support member; a display adapter coupled to the display cover; and at least one adjustment mechanism coupled to the display cover, wherein the adjustment mechanism comprises at least one mounting member that couples to the display adapter, wherein the mounting member comprises at least a first bracket element and a second bracket element; a lever that is slidably engaged within the first bracket element; and a biasing element supported by the second bracket element; wherein the biasing member cooperates with the lever such that, when a first force is applied to the lever the biasing member is compressed to enable the adjustment mechanism to be translated to a desired position.

Abstract: The present disclosure relates to an apparatus and a method for providing a plurality of motion vectors related to an image coded in a bitstream. The method includes obtaining a set of sample positions within the image, obtaining respective motion vectors associated with the set of sample positions, deriving an additional motion vector based on information coded in the bitstream, determining an additional sample position located within a triangle, which is formed by three sample positions of the set of sample positions, based on the respective motion vectors associated with the three sample positions, the triangle not including the rest of the sample positions of the set of sample positions, adding the additional sample position to the set of sample positions, and associating the derived additional motion vector with the additional sample position.

Abstract: A method for derivation of a temporal motion data (TMD) candidate for a prediction unit (PU) in video encoding or video decoding is provided. The derived TMD candidate is for inclusion in an inter-prediction candidate list for the PU. The method includes determining a primary TMD position relative to a co-located PU in a co-located largest coding unit (LCU), wherein the co-located PU is a block in a reference picture having a same size, shape, and coordinates as the PU, and selecting at least some motion data of a secondary TMD position as the TMD candidate when the primary TMD position is in a bottom neighboring LCU or in a bottom right neighboring LCU of the co-located LCU, wherein the secondary TMD position is determined relative to the co-located PU.

Abstract: A camera monitor system for a vehicle includes at least one forward facing camera that has a field of view that at least partially encompasses a route of forward travel of the vehicle. A camera monitor system (CMS) is configured to receive a video feed from the at least one forward facing camera. The CMS includes a processor and a memory, the memory stores instructions for causing the processor to identify a clearance object in the video feed, for causing the processor to determine a clearance height of the clearance object from the video feed, and compare the clearance height of the clearance object to a height of a trailer, and initiate a response in response to the clearance height of the object being less than or equal to the clearance height of the trailer.

Abstract: A video system includes a first data gathering node configured to receive a plurality of image streams from a plurality of cameras, respectively. Each of the plurality of cameras captures an environment of an autonomous driving vehicle (ADV). The first data gathering node tags the plurality of image streams with metadata that identifies each of the plurality of image streams, and combines the plurality of image streams with the metadata to form a combined image stream. A second data gathering node is communicatively coupled to the first data gathering node and is to receive the combined image stream from the first data gathering node and output the combined image stream with a second combined image stream.

Abstract: Aspects of the disclosure provide methods and apparatuses for video coding. A method for video decoding includes receiving a coded video bitstream that includes prediction information of a current block in a current picture. The prediction information indicates that an adaptive motion vector prediction (AMVP) mode and an adaptive motion vector resolution (AMVR) mode are applied to the current block. A set of motion vector (MV) resolutions in the AMVR mode is available for the current block. The method includes determining respective template matching (TM) costs corresponding to each of a plurality of MV resolutions in the set of MV resolutions based on the plurality of MV resolutions and motion information of the current block, reordering the plurality of MV resolutions based on the determined TM costs, selecting an MV resolution from the reordered plurality of MV resolutions, and reconstructing the current block based on the selected MV resolution.

Abstract: A display image is obtained by superimposing an image showing a vehicle on a captured image obtained by capturing an image on a rear side from the vehicle. For example, the image showing the vehicle is a computer graphics image. For example, a change is made in a superimposed positional relationship between the captured image and the image showing the vehicle in accordance with motion of a viewpoint of a driver. Since the display image is not only made from the captured image obtained by capturing an image on a rear side from the vehicle, but the display image is obtained by superimposing the image showing the vehicle on the captured image, it is possible to easily provide a sense of distance by motion parallax.

Abstract: An object detector detects, for each of environmental sensors mounted on a vehicle, an object in an area around the vehicle from each piece of time-series environmental data generated by the environmental sensor; identifies a blind spot that is not represented in any of the pieces of environmental data respectively generated by the environmental sensors; selects, from the environmental sensors, an environmental sensor generating environmental data that can be omitted in detection of the object, based on a travel condition of the vehicle; requests blind spot data representing the blind spot from an external device equipped with an external sensor capable of generating the blind spot data; and stops detection of the object from environmental data generated by the selected environmental sensor and detects an object in the blind spot from obtained blind spot data, when the blind spot data is obtained from the external device.

Abstract: An encoder includes circuitry and memory coupled to the circuitry. In operation, the circuitry encodes, per temporal sub-layer, one or more hypothetical reference decoder (HRD) parameters into an HRD-related supplemental enhancement information (SEI) message, the one or more HRD parameters being one or more parameters for an HRD, the one or more parameters being related to a decoding unit, the HRD-related SEI message being an SEI message related to the HRD.

Abstract: A vehicle with a road surface rendering function includes a projection member, a controller, and an external camera. The projection member is configured to project light for road surface rendering from the vehicle that is traveling to render a road surface rendered image on a road surface around the vehicle. The controller is configured to control light projection for the road surface rendering by the projection member. The external camera provided on the vehicle and configured to capture an image of the road surface so that the image includes surroundings of the road surface rendered image. The controller is configured to suppress the light projection from the projection member for the road surface rendered image by making determination on a road surface reflection state based on the image captured by the external camera.

Abstract: Methods, apparatus, systems and articles of manufacture to sample enabled views per atlas in immersive video are disclosed. An example apparatus includes an interface to obtain a bitstream corresponding to an immersive video; a bitstream analyzer to determine that metadata corresponding to an atlas of the bitstream identifies that at least part of a view of interest corresponds to the atlas, the metadata included in the bitstream; and a filter to generate a filtered bitstream by removing atlases that do not identify at least part of a view of interest from the bitstream, the interface to provide the filtered bitstream to a decoder.

Abstract: A data transmitter is to be mounted on an autonomous driving vehicle. The data transmitter determines whether a confidence score indicating the degree of reliability of detection of the object from the area image is greater than a predetermined confidence score threshold; transmits, when the confidence score regarding the area image is greater than the confidence score threshold, the area image or a face image representing the face of a driver to a terminal, together with a first setting for displaying the area image or the face image on the terminal in first mode; and transmits, when the confidence score is less than the confidence score threshold, the area image to the terminal, together with a second setting for displaying the area image on the terminal in second mode that draws more attention of a user of the terminal than the first mode.

Abstract: The technology relates to an exterior sensor system for a vehicle configured to operate in an autonomous driving mode. The technology includes a close-in sensing (CIS) camera system to address blind spots around the vehicle. The CIS system is used to detect objects within a few meters of the vehicle. Based on object classification, the system is able to make real-time driving decisions. Classification is enhanced by employing cameras in conjunction with lidar sensors. The specific arrangement of multiple sensors in a single sensor housing is also important to object detection and classification. Thus, the positioning of the sensors and support components are selected to avoid occlusion and to otherwise prevent interference between the various sensor housing elements.