Abstract: The present disclosure describes methods, device, and storage medium for obtaining lane line data of a road. The method includes obtaining and dividing, by a device, road-image data of a road into at least one segment. The device includes a memory storing instructions and a processor in communication with the memory. The method includes processing, by the device, each segment to obtain a two-dimensional grayscale image of each segment; extracting, by the device using a pre-trained deep neural network model, a lane line area and a lane line attribute in each two-dimensional grayscale image, to obtain a lane line area image of each segment; and splicing, by the device, each lane line area image based on corresponding road-image data and the lane line attribute, to obtain lane line data of the road.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for the generation and use of a surfel map with semantic labels. One of the methods includes receiving a surfel map that includes a plurality of surfels, wherein each surfel has associated data that includes one or more semantic labels; obtaining sensor data for one or more locations in the environment, the sensor data having been captured by one or more sensors of a first vehicle; determining one or more surfels corresponding to the one or more locations of the obtained sensor data; identifying one or more semantic labels for the one or more surfels corresponding to the one or more locations of the obtained sensor data; and performing, for each surfel corresponding to the one or more locations of the obtained sensor data, a label-specific detection process for the surfel.

Abstract: An apparatus suitable for at least to: receive, from a serving access node, a random access update precondition and a configuration with regard to a conditional handover, wherein the configuration indicates at least one handover candidate cell; carry out measurements according to the configuration, and if the random access update precondition is fulfilled, transmit a message to the serving access node, the message comprising information obtained by the measurements and indicating at least one beam of at least one handover candidate cell and/or at least one handover candidate cell that caused the random access update precondition being fulfilled for obtaining a random access resource configuration for carrying out the conditional handover.

Abstract: A method for motion prediction is provided. The method includes: capturing, by a single camera, a plurality of cameras or 3D software, images of an object at multiple angles to generate multi-view images of the object; synthesizing motion capture (MoCap) data according to the multi-view images; projecting a masking object onto the object to generate multi-view training images, wherein the multi-view training images are images in which parts of limbs of the object are unoccluded and other parts of the limbs of the object are occluded; and using the motion capture data and the multi-view training images to train a predictive model.

Abstract: A method of annotating road images, the method comprising implementing, at an image processing system, the following steps: receiving a time sequence of two dimensional images as captured by an image capture device of travelling vehicle; processing the images to reconstruct, in three-dimensional space, a path travelled by the vehicle; using the reconstructed vehicle path to determine expected road structure extending along the reconstructed vehicle path; and generating road annotation data for marking at least one of the images with an expected road structure location, by performing a geometric projection of the expected road structure in three-dimensional space onto a two-dimensional plane of that image.

Abstract: A device implementing a system for providing predicted RGB images includes at least one processor configured to obtain an infrared image of a subject, and to obtain a reference RGB image of the subject. The at least one processor is further configured to provide the infrared image and the reference RGB image to a machine learning model, the machine learning model having been trained to output predicted RGB images of subjects based on infrared images and reference RGB images of the subjects. The at least one processor is further configured to provide a predicted RGB image of the subject based on output by the machine learning model.

Abstract: The present disclosure discloses a building evacuation system and a building evacuation method. The evacuation method comprises: capturing image data of a region by a plurality of sensors to track a moving state of people in the region; detecting, in the moving state of the people being tracked, an object specified by at least one set abnormal mode, and matching the object with the abnormal mode; and generating an indication representing an abnormality of evacuation behavior based on the abnormal mode after being matched. The present disclosure can provide efficient evacuation.

Abstract: A vehicle may include a camera for capturing a region around the vehicle, a positioning sensor for measuring a position of the vehicle, a database for storing a precise map, and a learning data generating apparatus for generating data for learning based on the captured region, the position of the vehicle, and the precise map.

Abstract: An image processing system includes: a possibility determination unit that determines whether there is a possibility that an obstacle is shown in an image acquired by an image acquisition device of a vehicle; a transmitting unit that transmits, from the vehicle, image information of the acquired image if it has been determined that there is a possibility that an obstacle is shown therein; a receiving unit that receives the image information from vehicles; a processing unit that performs image processing to identify an obstacle shown in the acquired image; and a duplication determination unit that determines whether or not an identified obstacle, which has been identified in a previous acquired image, is shown in a subsequent acquired image received by the receiving unit, wherein the processing unit performs the image processing on the subsequent acquired image if the subsequent acquired image has been determined to not show the identified obstacle.

Abstract: One example method of operation may include receiving one or more data messages, identifying calls and corresponding call data from the one or more messages, identifying call parameters from the call data, applying a call activity filter criteria to the call parameters to identify a suspect sub-set of the call parameters which indicate an elevated likelihood of call scam, forwarding the call parameters and the suspect sub-set of call parameters to one or more call data tables, and assigning one or more scam designation threshold scores to the suspect sub-set of the call parameters in the one or more call data tables.

Abstract: An image processing apparatus that records a high dynamic range (HDR) signal as a file. The apparatus acquires information indicating peak luminance corresponding to one output dynamic range, of a plurality of different output dynamic ranges, in accordance with shooting settings of the HDR signal. The apparatus then records a first value based on the acquired information to the file along with the HDR signal.

Abstract: Systems, devices, methods, and computer-readable media for image processing by machine learning are provided. A method includes providing, as input to a first machine learning (ML) model trained based on image and corresponding depth data, data of a first image, the first image captured by a sensor of a first modality. The method includes receiving, from the ML model, an estimated depth per pixel of the first image. The method includes providing, as input to a second ML model trained based on the first image and a loss in constructing an estimated second image in a second modality, the first image and receiving, from the second ML model, estimated transformation parameters that transform the first image from the first modality to the second modality. The method includes using the estimated transformation parameters and the estimated depth to generate an estimated second image in the second modality.

Abstract: A system for detecting damage to a glass surface particularly vehicle glazing panels such as vehicle windscreens. The system uses a sensor unit disposed proximate the surface and a processor in communication with the sensor unit. The processor is configured to analyse data received from the sensor unit in order to determine the integrity of the surface and a communication unit is configured to output a signal in response to the processor determining that the surface has been damaged. For vehicle glass the system is preferably integrated into the vehicle management and control systems such that the system is active when the vehicle is active or moving. The management and or control system may monitor for instances or situations when changes, such as above threshold changes, occur in order to produce an output warning signal.

Abstract: A computing device is programmed to generate a plurality of raw 3D point clouds from respective sensors having non-overlapping fields of view, scale each of the raw point clouds including scaling real-world dimensions of one or more features included in the respective raw 3D point cloud, determine a first transformation matrix that transforms a first coordinate system of a first scaled 3D point cloud of a first sensor to a second coordinate system of a second scaled 3D point cloud of a second sensor, and determine a second transformation matrix that transforms a third coordinate system of a third scaled 3D point cloud of a third sensor to the second coordinate system of the second scaled 3D point cloud of the second sensor.

Abstract: A data capture system includes: a first capture node including: a first set of image sensors, and a first computing device connected with the first set of image sensors and configured to: control the first set of image sensors to capture respective images of an object within a capture volume; generate a first point cloud based on the images; and transmit the first point cloud to a data capture server for dimensioning of the object; and a second capture node including: a second set of image sensors, and a second computing device connected with the second set of image sensors and configured to: control the second set of image sensors to capture respective images of the object; generate a second point cloud based on the images; and transmit the second point cloud to the data capture server.

Abstract: The present disclosure involves expanding the dynamic range of low dynamic range images and concerns obtaining a first expansion exponent map for an image, and determining, for each pixel of the image, an expanded luminance value by performing an exponentiation with an expansion exponent value determined from the first expansion exponent map on a luminance value of the pixel, and can include calculating, for the pixel of the image, an expansion correcting value by using a modulating function that takes as input a value representative of the luminance of the pixel and is an increasing function whose increase is higher for higher input values, and subtracting the expansion correcting value from the expansion exponent value of the first expansion exponent map.

Abstract: An information processing apparatus, a data generation method, and a program capable of obtaining useful information about a person from video data are provided. An information processing apparatus (1) according to an example embodiment includes a base-information acquisition unit (2) that acquires a plurality of types of pieces of base information based on video data in which at least one person is shown, the pieces of base information being pieces of information used to monitor a person, and a base-information integration unit (3) that generates integrated information by integrating, among the plurality of pieces of base information, those that satisfy a predetermined relation as information of one and the same person.

Abstract: An information processing apparatus includes a reception section that receives an editing instruction with respect to an arrangement configuration of a still image including plural pages, and a generation section that generates a moving image which corresponds to the arrangement configuration of the still image edited due to the editing instruction and which is acquired through combination with a moving image including playback sections corresponding to the still image.

Abstract: The invention describes a method (100) for counterfeit detection using a portable device (1) with installed counterfeit detection application, to a data carrier (30) comprising this counterfeit detection application, to the portable device (1) used in this method and to a cover (50) comprising guiding structures to perform this method comprising the steps of taking multiple overlapping pictures (110) from at least a portion of the object (10) with the camera (2) of the portable device (1) positioned in front of the object (10) during relatively moving (RM) the portable device with respect to and (1) along the object (10); combining (120) all taken pictures to a single combined image of at least the portion of the object (10) with increased resolution by the counterfeit detection application (4) executed on the portable device (1); applying image processing (130) to the combined image by the counterfeit detection application (4) providing an improved image with improved properties compared to the combined imag

Abstract: An acquired image is analysed to determine a test outcome value. A shape template for a test structure is provided to identify a position of a target measurement region on the test structure. A mapping defining a transformation of the shape template onto the image frame is determined. A mapping is determined and it is determined if a first matching condition based on first displacements of one or more edges identified in the image frame relative to the shape template is satisfied for the mapping. When the mapping satisfies the first matching condition and a second different matching condition based on second displacements of one or more edges identified in the image frame relative to the shape template, a verified image of a test structure is established. In the verified image of the test structure a target measurement region is identified. A test outcome value is determined by analysing the target measurement region.