Abstract: System and method for image processing are provided. A stream of images may be obtained, for example by capturing images using an image sensor. Points in time associated with an activity may be obtained. For each point in time, the stream of images may be analyzed to identify events related to the activity and preceding the point in time. Based on the identified events, an event detection rule configured to analyze images to detect at least one event may be obtained. Image data may be obtained, and the image data may be analyzed using the event detection rule to detect events matching selected criteria in the image data.

Abstract: A cloud detection method based on Landsat 8 snow-containing image, including the following steps: Step 1, selecting any Landsat 8 image as a current image; Step 2, obtaining a cloud threshold for delineating a cloud range from the current image; and Step 3, removing false anomalies in the cloud range delineated by the cloud threshold from the current image so as to obtain a cloud image from which the false anomalies have been removed. The present disclosure can effectively solve the problem of confusion of cloud and snow present in conventional cloud detection methods, and is applicable to regions of different latitudes, without limitations by the amount of cloud.

Abstract: An information processing apparatus of the present invention detects a queue (20) of objects from video data (12). Further, the information processing apparatus of the present invention generates element information using a video frame (14) in which the queue (20) of objects is detected. The element information is information in which an object area (24) in the video frame (14) occupied by the object (22) included in the queue (20) of objects is associated with an attribute of the object (22). Furthermore, the information processing apparatus of the present invention detects a change in the queue (20) of objects based on the element information and the detection result of the object to video frame (14) generated after the video frame (14) in which the element information is generated. Then, the information processing apparatus of the present invention generates element information for the queue (20) of objects in which a change is detected to update the element information used later.

Abstract: Disclosed is a device having a processor, a sensor and a computer-readable storage device storing instructions which, when executed by the processor, cause the processor to perform operations including receiving an interaction with the device indicating an intent of a user of the device to initiate a function, sensing, via the sensor, a condition associated with the device, and determining, based on the condition, a probability of whether the user intended to initiate the function using the device to yield a determination. When the determination indicates that the condition causes a sufficient probability to exist at a threshold that the user did not intend to initiate the function, the instructions prevent the device from initiating the function. When the determination indicates that the condition does cause a sufficient probability to exist at the threshold that the user did intend to initiate the function, the instructions initiate the function on the device.

Abstract: Embodiments of this disclosure provide a lane detection apparatus and method and an electronic device. First, preprocessing is performed based on semantic segmentation to remove interference objects in a binary image, which may improve accuracy of a lane line detection and may be applicable to various road scenarios, and the result based on semantic segmentation may automatically extract a lane line region image containing one or more lane lines, thereby automatically performing perspective transformation to perform search and fitting on the one or more lane lines, including achieving multi-lane detection. And furthermore, by synthesizing detection results of a plurality of input images, accuracy and integrity of the lane detection may further be improved.

Abstract: The present embodiments relate to analysing an image. An artificial deep neural net is pre-trained to classify images into a hierarchical system of multiple hierarchical classes. The pre-trained neural net is then adapted for one specific class, wherein the specific class is lower in the hierarchical system than an actual class of the image. The image is then processed by a forward pass through the adapted neural net to generate a processing result. An image processing algorithm is then used to analyse the processing result focused on features corresponding to the specific class.

Abstract: An example apparatus for mining multi-scale hard examples includes a convolutional neural network to receive a mini-batch of sample candidates and generate basic feature maps. The apparatus also includes a feature extractor and combiner to generate concatenated feature maps based on the basic feature maps and extract the concatenated feature maps for each of a plurality of received candidate boxes. The apparatus further includes a sample scorer and miner to score the candidate samples with multi-task loss scores and select candidate samples with multi-task loss scores exceeding a threshold score.

Abstract: An image registration method, an image registration device, and a storage medium. The image registration method includes: causing a display device to display at least one spot array; obtaining a feature image, and performing a feature-based image registration operation on the feature image to obtain at least one transformed image; and obtaining a mapping model based on the at least one transformed image. The feature image is an image which is shown on the display device and displays the at least one spot array.

Abstract: An object in a digital image is automatically recognized by obtaining the digital image, generating a first vector representation of a plurality of pixels of the obtained digital image, randomizing the first vector representation to generate a first generalized vector representation of the digital image that is substantially an order of magnitude smaller than the first vector representation, and searching a repository of hierarchically generalized vector representations of previously recognized digital images, to determine whether the first generalized vector representation of the digital image matches one or more of the previously recognized digital images, within a predetermined threshold value, based on determining a focus area within the obtained digital image, using associative memory.

Abstract: Method for the calculation resource-saving semantic segmentation of image data of an imaging sensor with the aid of an artificial neural network, in particular, of a convolutional neural network, the artificial neural network including an encoder path, a decoder path, the encoder path transitioning into the decoder path, the transition taking place via a discriminative path, the following steps taking place in the discriminative path: dividing an input tensor as a function of a division function into at least one first slice tensor and at least one second slice tensor, the input tensor originating from the encoder path; connecting the at least one first slice tensor to the at least one second slice tensor as a function of a connection function in order to obtain a class tensor; and outputting the class tensor to the decoder path of the neural network.

Abstract: A method for the calculation resource-saving semantic segmentation of image data of an imaging sensor with an artificial neural network, in particular, of a convolutional neural network, the artificial neural network including an encoder path, a decoder path (and a skip component), including: initial connection (merge) of an input tensor to a skip tensor with an initial connection (merge) function/connection instruction to obtain a merged tensor, the input tensor and the skip tensor being dependent on the image data; application of a function of a neural network, in particular, of a convolution to the merged tensor to obtain a proof reader tensor; second connection (merge) of the proof reader tensor to the input tensor with a second connection (merge) function/connection instruction to obtain an output tensor; outputting the output tensor to the decoder path of the artificial neural network.

Abstract: A computer platform implements a precision agriculture system that predicts output conditions, such as diseases, salt damage, soil problems, water leaks and generic anomalies, for orchards under analysis. The computer platform stores site and crop datasets and processed satellite image for the orchards. An orchard data learned model predicts a propensity for existence of output conditions associated with the permanent crops based on the data values for the variables of the site and crop datasets. Also, a satellite model predicts a propensity for existence of the output conditions at the orchard based on processed satellite images. A precision agriculture management model is disclosed that integrates the orchard data learned model with the satellite model to accurately predict the output conditions.

Abstract: Various embodiments of the disclosure relate generally to an electronic device and its operating method for creating a calibration condition of an in-display fingerprint sensor and calibrating the fingerprint sensor according to the created condition, using a touchscreen display.

Abstract: A method for detecting and recognizing objects in images includes obtaining a video stream and pre-processing the video stream to obtain an image queue arranged in a frame playing order and storing the image queue into a storage device. An image frame of the image queue from the storage device is read and at least one object in the image frame is detected and recognized. An image recognition device is also provided.

Abstract: The present invention seeks to provide a method of analyzing medical image, the method comprises receiving a medical image; applying a model stored in a memory; analyzing the medical image based on the model; determining the medical image including a presence of fracture; and, transmitting an indication indicative of the determination.

Abstract: A method for reconstructing an imprint image, from a set of image portions, includes the steps of: extracting, from each image portion, a set of local points of interest and, for each point of local interest, calculating a descriptor vector that characterizes said point of local interest; for each pair of two image portions, evaluating a local interest points association score representative of a probability that the two image portions are contiguous on the imprint image; assembling the image portions of a best pair to form an assembled fragment; repeating the above steps by replacing each time, in the set of image portions, the two image portions of the best pair, until all the association scores of the remaining pairs are less than or equal to a predetermined threshold, and producing an assembly map of the image portions; merging the image portions to reproduce the imprint image.

Abstract: A computer-implemented method for estimating head pose angles of a user includes determining a first rotation between a first head pose axis associated with a first image of a plurality of images of the user and a camera axis associated with a camera taking the images. A second rotation is determined between a second head pose axis associated with a second image of the user and the camera axis. The first and second head pose axes are determined based on light reflections within the plurality of images. A head pose angle of the user can be estimated based on the first rotation and the second rotation. An alert can be generated based on the estimated head pose angle.

Abstract: Disclosed are various embodiments that extract vehicle trajectories from aerial videos. A vehicle track comprising pixel coordinate points is obtained. The pixel coordinate points are converted to relative coordinate points. At least one vehicle trajectory is extracted based at least in part on the vehicle track and the relative coordinate points. A lane structure is generated that is based on the at least one vehicle trajectory.

Abstract: An apparatus and method for imaging quality assessment of an imaging system employs an aggregate phantom and a processor for imaging analysis. The aggregate phantom includes a plurality of self-contained sections configured to be moved independently and re-assembled in the imaging system. Each section includes fiducial features of known relative location. The processor: quantitatively determines location of the fiducial features within an image of the aggregate phantom; compares the determined location within the image to the known relative location of the fiducial features to produce a distortion field; and distinguishes between actual geometric distortion of the imaging system and rigid-body transformations of sections of the aggregate phantom, in the distortion field. For extended fields-of-view, the aggregate phantom may be repositioned, and sets of images combined to determine a distortion field of the extended image.

Abstract: A locating system that performs a locating method for locating a flame-cut billet in a stack of flame-cut billets that includes an imager that obtains an image of an end surface of a billet, a classifier that classifies the image of the end surface, and a matcher that matches the classified image of the end surface with a classified image from among a plurality of classified images stored in a classified image storage.