Abstract: A computer-implemented method for image capture by a mobile device, comprising: receiving, by a video capturing application running on a mobile device, a video stream from a camera of the mobile device; identifying a specific frame of the video stream; generating a plurality of hypotheses defining image borders within the specific frame; selecting, by a neural network, a particular hypothesis among the plurality of hypotheses; producing a candidate image by applying the particular hypothesis to the specific frame; determining a value of a quality metric of the candidate image; determining that the value of the quality metric of the candidate image exceeds one or more values of the quality metric of one or more previously processed images extracted from the video stream; wherein the image capture application is a zero-footprint application.

Abstract: Systems and methods of the present disclosure can facilitate determining a three-dimensional surface representation of an object. In some embodiments, the system includes a computer, a calibration module, which is configured to determine a camera geometry of a set of cameras, and an imaging module, which is configured to capture spatial images using the cameras. The computer is configured to determine epipolar lines in the spatial images, transform the spatial images with a collineation transformation, determine second derivative spatial images with a second derivative filter, construct epipolar plane edge images based on zero crossings of second derivative epipolar planes image based on the epipolar lines, select edges and compute depth estimates, sequence the edges based on contours in a spatial edge image, filter the depth estimates, and create a three-dimensional surface representation based on the filtered depth estimates and the original spatial images.

Abstract: In variants, the method for automatic debris detection includes: determining a region image; optionally determining a parcel representation for the region image; generating a debris representation using the region image; generating a debris score based on the debris representation; and optionally monitoring the debris score over time.

Abstract: Disclosed is an electronic apparatus. The electronic apparatus includes a processor configured to downscale an image using a trained first artificial intelligence (AI) model and to encode a downscaled image, and the processor is configured to control downscaling of the image based on quality information of the image obtained using a trained second AI model, and the second AI model may be trained using feature information of the image obtained from the first AI model.

Abstract: [Object] To provide the identification device that performs identification accurately without being affected by variations in ambient light and an electronic device. [Solution] Provided is an identification device including: a direct reflected light information calculation unit configured to calculate, on the basis of sensing data by a TOF sensor that applies light to an object to detect the light, direct reflected light information about direct reflected light from the object; an object detection unit configured to detect the object on the basis of the direct reflected light information; and an object identification unit configured to identify the object on the basis of the direct reflected light information about the object detected.

Abstract: Provided is an information processing device configured to: acquire an image captured according to an imaging instruction by an imaging device mounted to a mobile object; acquire sensor information including position information about the mobile object from a sensor device according to a signal transmitted from the imaging device in response to the imaging instruction; and associate the acquired sensor information with the acquired image.

Abstract: Provided are an image processing apparatus, an image processing method, and a moving body that enable removal of noise in distance images. A distance image having a pixel value corresponding to a distance to an object and an intensity image having a pixel value corresponding to the received light intensity of light reflected from the object that are taken at the same angle are acquired, and a pixel value of a pixel in the distance image that corresponds to a pixel having a pixel value smaller than a predetermined threshold in the intensity image is converted into a no-distance pixel. Noise in the distance image is removed in this way.

Abstract: An advanced driver assistance apparatus, a vehicle having the same, and a method of controlling the vehicle are provided. The vehicle may acquire a first image of a road by a first image acquisition unit while traveling, acquire a second image of the road by a second image acquisition unit while traveling, recognize a first lane in the first image by a first lane recognizer, recognize a second lane in the second image by a second lane recognizer, determine whether at least one of the first lane recognizer or the first image acquisition unit has a failure by comparing the first lane with the second lane, and output failure information when at least one of the first lane recognizer or the first image acquisition unit is determined to have the failure.

Abstract: Embodiments of the present disclosure relate to a method and apparatus for outputting information. The method may include: acquiring point cloud data and image data collected by a vehicle during a driving process; determining a plurality of time thresholds based on a preset time threshold value range; executing following processing for each time threshold: identifying obstacles included in each point cloud frame and each image frame respectively; determining a similarity between the obstacles; determining, in response to the similarity being greater than a preset similarity threshold, whether a time interval between the point cloud frame and the image frame corresponding to two similar obstacles is less than the time threshold; and processing recognized obstacles based on a determining result, to determine the number of obstacles; and determining, based on a plurality of numbers, and outputting a target time threshold.

Abstract: Provided is an information processing apparatus and an information processing method capable of reflecting a feeling of an image capturing person for each subject of a captured image in the captured image and reproducing the realistic feeling at the time of capturing. An information processing apparatus including a recognition unit that recognizes one or more subjects from a captured image, an estimation unit that estimates a feeling of an image capturing person for each of the recognized subjects on the basis of data regarding a line-of-sight of the image capturing person and sensor data of the image capturing person associated with the captured image, and an image processing unit that performs image processing of reflecting the feeling for each of the subjects in the captured image.

Abstract: The three-dimensional measurement apparatus includes a light projecting unit projects, onto a target, a pattern in which data is encoded, an image capturing unit captures an image of the target onto which the pattern is projected, and a calculation unit calculates positions of a three-dimensional point group based on positions of the feature points and the decoded data, in which the pattern includes unit patterns that each expresses at least two bits and are used in order to calculate the positions of the three-dimensional point group, the unit patterns each includes a first region and a second region that has an area that is larger than an area of the first region, and an area ratio between the first region and the second region is at least 0.3 and not more than 0.9.

Abstract: A fingertip detection method, a fingertip detection device and a storage medium are disclosed. The fingertip detection method includes: determining a minimum-depth point in a hand area to be detected based on a depth image; determining a hand vertex in the hand area to be detected based on the depth image; determining a fingertip position based on the minimum-depth point and the hand vertex.

Abstract: An image processing method, an apparatus, a non-transitory computer readable storage medium and an electronic device are disclosed. The method includes: acquiring an accuracy level of a target application in response to an image collecting instruction initiated by the target application; adjusting an accuracy of an image to be sent according to the accuracy level, and obtaining a target image; and sending the target image to the target application.

Abstract: Described is a technique for optimization an image for facial detection. More specifically, described is a process of predicting the location of a face within an image and adjusting image settings based on at least a portion of the predicted location of the face. An image may be adjusted based on the characteristics of a metering region, which may be selected prior to performing facial detection. For example, the metering region may be a specified shape with dimensions equal to a certain percentage of the input image and placed at a specified location. The result of using such a metering region is that the image adjustments may be based on a portion of the face, and therefore, may be optimized for facial detection.

Abstract: A system for determining candidate answers during an interview. The system may include a memory storing executable instructions, and at least one processor configured to execute the instructions to perform operations. The operations may include capturing, by an image sensor, a plurality of images comprising a plurality of candidate answers; detecting, based on the captured images, a first bounding box comprising the plurality of the candidate answers; detecting, based on the captured images, a second bounding box comprising a plurality of alphanumeric characters, a first one of the alphanumeric characters being located on a line of software code; calculating a distance from a side of a first bounding box to a side of a second bounding box; and determining, based on the calculated distance, a source code alignment.

Abstract: Disclosed herein are system, method, and computer program product embodiments for querying document terms and identifying target data from documents. In an embodiment, a document processing system may receive a document and a query string. The document processing system may perform optical character recognition to obtain character information and positioning information for the characters of the document. The document processing system may generate a two-dimensional character grid for the document. The document processing system may apply a convolutional neural network to the character grid and the query string to identify target data from the document corresponding to the query string. The convolutional neural network may then produce a segmentation mask and/or bounding boxes to identify the targeted data.

Abstract: The present disclosure provides an expression recognition method, a computer device, and a computer-readable storage medium. The expression recognition method includes: obtaining a facial image to be recognized; preprocessing the facial image to be recognized to obtain a preprocessed facial image; obtaining a first output image according to the preprocessed facial image, wherein the first output image at least represents a texture feature of the facial image to be recognized; obtaining a second output image according to the first output image, wherein the second output image at least represents a structural feature of organs of the facial image to be recognized; and determining an expression category corresponding to the facial image to be recognized, according to the second output image.

Abstract: The embodiment of the present disclosure provides an image identification system and an image identification method, and relates to the field of identification technology for improving the classification accuracy of the existing image classification model.

Abstract: A hyperspectral analysis computer device is provided. The hyperspectral analysis computer device includes at least one processor in communication with at least one memory device. The hyperspectral analysis computer device is configured to store a plurality of spectral analysis data, receive at least one background item and at least one item to be detected from a user, generate one or more spectral bands for analysis based on the at least one background item, the at least one item to be detected, and the stored plurality of spectral analysis data, receive one or more mission parameters from the user, and determine a probability of success based on the one or more mission parameters and the generated one or more spectral bands.

Abstract: A method, apparatus and a system for human body tracking processing, where an apparatus for video collection processing in the system has a built-in intelligent chip, and before uploading video data to a cloud server, the intelligent chip performs a pre-processing on the video data, retains a key image frame and performs a human body detection and a tracking processing on the key image frame by using human body detection tracking algorithm to acquire a first human body detection tracking result. Afterwards, the intelligent chip sends the first human body detection tracking result to the cloud server, so that the cloud server performs a human body re-identification algorithm processing and/or three-dimensional reconstruction algorithm processing on the first human body detection tracking result to acquire a second human body detection tracking result.