Abstract: An object tracking method includes: obtaining a video stream acquired by a camera, and decoding the video stream to obtain a plurality of image frames; and obtaining position information of a target object in a current image frame. Obtaining the position information of the target object in the current image frame includes: performing, in response to that the current image frame is a first-type image, object detection on the current image frame to obtain the position information of the target object in the current image frame; and predicting, in response to that the current image frame is a second-type image, the position information of the target object in the current image frame based on motion vectors of a previous image frame and a position the target object in the previous image frame.

Abstract: An image processor includes an edge detection portion for scanning an image and detecting, as edges, an arrangement of pixels in which brightness value difference or color parameter difference between the pixels is equal to or greater than a threshold; a grouping portion for grouping the detected edge based on edge length, a distance between endpoints of the edges, and an angle between the edges; a determination portion for determining the grouped edges as a dashed line edge group when a pattern, in which the brightness value difference or the color parameter difference between the pixels is detected, matches a predetermined pattern; a correction portion for performing a linear approximation process on the dashed line edge group to correct a coordinate value of an endpoint of the dashed line edge; and a parking frame setting portion for setting a parking frame using the corrected dashed line edge.

Abstract: A system includes an image sensor having a plurality of pixels that form a plurality of regions of interest (ROIs), and configured to operate at a frame rate higher than a threshold rate. The system also includes an image processing resource. The system further includes control circuitry configured to perform operations that include obtaining, from the image sensor, a full-resolution image of an environment. The full-resolution image contains each respective ROI of the plurality of ROIs. The operations also include selecting a particular ROI based on the full-resolution image, and detecting an object of interest in the particular ROI. The operations include determining a mode of operation by which subsequent image data generated by the particular ROI is to be processed. The operations further include processing, based on the mode of operation and the frame rate, the image data comprising a plurality of ROI images of the object of interest.

Abstract: The disclosure is detecting an authentication target who is moving in a predetermined direction in a video; inputting a first image in which an entire body of the target; calculating characteristic information from an image of the entire body in the first image, comparing the calculated characteristic information with characteristic information of the entire body stored in first memory that stores characteristic information of entire bodies of targets, and extracting candidate information of the targets from the first memory based on a first authentication result; inputting a second image in which an iris of the target; and comparing characteristic information of irises stored in second memory that stores the characteristic information of the irises of targets with characteristic information of an iris from the second image, calculating a verification score, executing second authentication on the target in the second image based on the verification score, and outputting an authentication result.

Abstract: Techniques for enhancing an image are described. For example, a lower-resolution image from a video file may be enhanced using a trained neural network applying the trained neural network on the lower-resolution image to remove artifacts by removing artifacts by generating, using a layer of the trained neural network, a residual value based on the proper subset of the received image and at least one corresponding image portion of a preceding lower resolution image in the video file and at least one corresponding image portion of a subsequent lower resolution image in the video file, upscale the lower-resolution image using bilinear upsampling, and combine the upscaled received image and residual value to generate an enhanced image.

Abstract: The presented invention includes the generation of cloud points, the identification of objects in the cloud points, and, in this case, finding the positions of objects in cloud points. In addition, the invention includes capturing images, data streaming, and digital image processing in different points of the system, and calculation of the position of objects. The invention includes the usage of cameras of mobile smart devices, smart glasses, 3D cameras, but not necessarily. The data streaming provides video streaming and sensor data streaming from mobile smart devices. The presented invention further includes cloud points of buildings in which the positioning of separated objects could be implemented. It also consists of the database of cloud points of isolated objects which help to calculate the position in the building. Finally, the invention comprises the method of objects feature extraction, comparing in the cloud points and position calculation.

Abstract: An operating method of a slope estimating apparatus is provided. The operating method of the slope estimating apparatus including at least one camera includes obtaining a forward image through the at least one camera, detecting a lane included in the forward image, dividing the forward image into a plurality of smaller regions in a horizontal direction, identifying a plurality of lane segments included in each of the plurality of smaller regions, obtaining a plurality of coordinate values forming each of the plurality of lane segments, and obtaining a pitch angle of each of the plurality of smaller regions based on the obtained plurality of coordinate values.

Abstract: Various embodiments described herein are directed towards authenticating calls by using one or more keys associated with a specific user. In examples, the user is the sender of a call. In various embodiments, when a call is made, an identifying payload is encrypted using a private key associated with the user. The encrypted identifying payload is appended to the call data stream. The identifying payload may be decrypted with a public key. In embodiments, the identifying payload may be verified. In various embodiments, further authentication methods may be performed by using an object such as a contactless card to provide one or more components of the identifying payload and/or keys. In embodiments, a connection may be made between the sender and the intended recipient of a call based on the verification of the identifying payload.

Abstract: A video generation system is described that extracts one or more characters or other objects from a video, re-animates the character, and generates a new video in which the extracted characters. The system enables the extracted character(s) to be positioned and controlled within a new background scene different from the original background scene of the source video. In one example, the video generation system comprises a pose prediction neural network having a pose model trained with (i) a set of character pose training images extracted from an input video of the character and (ii) a simulated motion control signal generated from the input video. In operation, the pose prediction neural network generates, in response to a motion control input from a user, a sequence of images representing poses of a character. A frame generation neural network generates output video frames that render the character within a scene.

Abstract: A computer device extracts a plurality of target windows from a target video. Each of the target windows comprises a respective plurality of consecutive video frames. For each of the target windows, the device performs action recognition on the respective plurality of consecutive video frames corresponding to the target window to obtain respective first action feature information of the target window. The device obtains a similarity between the first action feature information of the target window and preset feature information. The device determines, from the respective obtained similarities corresponding to the plurality of target windows, a highest first similarity and a first target window corresponding to the highest first similarity. The device also determines a dynamic action corresponding to the highest first similarity as the preset dynamic action in accordance with threshold settings.

Abstract: An apparatus enables communication between a user device and a communication server. The apparatus receives a device identifier of the user device and determines after searching a device-to-token database that the device identifier is not associated with any device communication token. The apparatus activates a predetermined application on the user device, and thereafter receives a device communication token of the predetermined application. A mapping of the device communication token with the device identifier is stored in the device-to-token database after which a communication account is created for the user device on a communication server. A login credential for the communication account is sent to the user device in a message addressed to the predetermined application and transmitted via a message server. The predetermined application on the user device receives the message, and thereafter automatically logs in to the communication server according to the login credential in the message.

Abstract: A method for a wireless device to establish an RRC connection with a network for accessing a network slice of the network is provided. The method receives, from the network, an access control parameter configuration of an access category associated with the network slice while the wireless device is in a Radio Resource Control (RRC) inactive state (RRC INACTIVE). The method then initiates a random access procedure for establishing the RRC connection with the network to access the network slice according to an access control indicator of the access control parameter configuration of the access category.

Abstract: An image processing apparatus extracts a foreground image corresponding to an object included in a processing image using a background image corresponding to the processing image, and generates the background image from the processing image. The image processing apparatus determines whether it is allowed to update the background image for use in the extraction, and based on a result of the determination, updates the background image for use in the extraction using the generated background image.

Abstract: A processor-implemented method with liveness detection includes: receiving a plurality of phase images of different phases; generating a plurality of preprocessed phase images by performing preprocessing, including edge enhancement processing, on the plurality of phase images of different phases; generating a plurality of differential images based on the preprocessed phase images; generating a plurality of low-resolution differential images having lower resolutions than the differential images, based on the differential images; generating a minimum map image based on the low-resolution differential images; and performing a liveness detection on an object in the phase images based on the minimum map image.

Abstract: A method includes receiving, by a computing device, acceleration information from an acceleration sensor attached to a product; receiving, by the computing device, from an image capture device an image of a prospective purchaser of the product; determining, by the computing device, a movement of the prospective purchaser based on the acceleration information and the image, the movement being in relation to a movement of the product; and sending, by the computing device, display information to a digital display, the display information including information related to the product. The movement of the product is based on the acceleration information.

Abstract: Disclosed are a device and a method for allocating physical cell identifier (PCI) of a mobile base station. The device comprises: an acquiring unit configured to acquire location and movement speed of the mobile base station; a determining unit configured to determine a valid time interval for PCI of the mobile base station based on at least one of the location and the movement speed; an information collection unit configured to collect information relating to network configuration within a predetermined range where the mobile base station is located when the valid time interval is expired; and a PCI determining unit configured to determine the PCI of the mobile base station based on the information relating to network configuration within the predetermined range where the mobile base station is located.

Abstract: An example method for controlling an external electronic device of an electronic device, according to various embodiments, includes: receiving data information corresponding to at least one function of the external electronic device from an external electronic device connected to the electronic device; displaying a setting window for setting a user interface for controlling the external electronic device using the data information; selecting a control item corresponding to the at least one function included in the setting window according to user input reception; and setting and displaying the user interface corresponding to the selected control item.

Abstract: Systems and methods for image-based perception. The methods comprise: obtaining, by a computing device, images captured by a plurality of cameras with overlapping fields of view; generating, by the computing device, spatial feature maps indicating locations of features in the images; defining, by the computing device, predicted cuboids at each location of an object in the images based on the spatial feature maps; and assigning, by the computing device, at least two cuboids of said predicted cuboids to a given object when predictions from images captured by separate cameras of the plurality of cameras should be associated with a same detected object.

Abstract: An information processing apparatus includes: a memory; and a processor coupled to the memory and the processor configured to: acquire a plurality of sample videos; identify a position and time at which an attribute appears in each of the plurality of sample videos, the attribute being output by each of one or more pre-trained models to which each of the plurality of sample videos is input; cluster attribute labels based on the position and time of the attribute for each of the plurality of sample videos; and generate a rule by combining attribute labels included in a cluster having a highest frequency of appearance among cluster groups obtained for all of the plurality of sample videos.

Abstract: A luminance determining unit 14 determines a luminance distribution of an exterior circumstantial image in a line-of-sight direction of a driver 300, and a luminance changing unit 15 determines a bright region 301 of this luminance distribution. Further, the luminance changing unit 15 determines a luminance after the change in a peripheral region 302 of this bright region 301. A virtual-image creating unit 16A creates a virtual image based on the determined luminance, and a display processing unit 17 displays this virtual image on a display unit 200. In this manner, since a display system 1A displays the virtual image for use in increasing the luminance in periphery of the bright region 301, the feeling of the brightness for the driver 300 can be moderated, and therefore, the visual recognition can be improved. That is, the display system 1A can output the virtual image depending on the circumstances.