Abstract: Aspects of the current disclosure include systems and methods for identifying an entity in a query image by comparing the query image with digital images in a database. In one or more embodiments, a query feature may be extracted from the query image and a set of candidate features may be extracted from a set of images in the database. In one or more embodiments, the distances between the query feature and the candidate features are calculated. A feature, which includes a set of shortest distances among the calculated distances and a distribution of the set of shortest distances, may be generated. In one or more embodiments, the feature is input to a trained model to determine whether the entity in the query image is the same entity associated with one of the set of shortest distances.

Abstract: According to one embodiment, a position and attitude estimation device includes a processor. The processor is configured to acquire time-series images continuously captured by a capture device installed on a mobile object, estimate first position and attitude of the mobile object based on the acquired time-series images, estimate a distance to a subject included in the acquired time-series images and correct the estimated first position and attitude to a second position and attitude based on an actual scale, based on the estimated distance.

Abstract: A first six degree-of-freedom (DoF) pose of an object from a perspective of a first image sensor is determined with a neural network. A second six DoF pose of the object from a perspective of a second image sensor is determined with the neural network. A pose offset between the first and second six DoF poses is determined. A first projection offset is determined for a first two-dimensional (2D) bounding box generated from the first six DoF pose. A second projection offset is determined for a second 2D bounding box generated from the second six DoF pose. A total offset is determined by combining the pose offset, the first projection offset, and the second projection offset. Parameters of a loss function are updated based on the total offset. The updated parameters are provided to the neural network to obtain an updated total offset.

Abstract: A method and computer software for creating an encoded image and which can optionally include a method for decoding the encoded image. The encoded image is preferably formed from at least one symmetric image but can be formed from a plurality of symmetric images. Embodiments of the present invention can be performed with physical paper and writing utensils or can be performed via computer software. Embodiments of the present invention can be used for art authentication based on results obtained by decoding an image. In one embodiment, one or more encoded image elements can be revealed simultaneously. Optionally, however, encoded image elements can be caused to be revealed in a series that gives a sense of motion in a manner similar to that of motion picture animation.

Abstract: A method to compute a variable number of image planes, which are selected to better represent the scene while reducing the artifacts on produced novel views. This method analyses the structure of the scene by means of a depth map and selects the position in the Z-axis to split the original image into individual layers. The method also determines the number of layers in an adaptive way.

Abstract: One aspect relates to a computer-implemented method for determining a skeleton of point cloud data in an automotive system for monitoring the environment of a vehicle. In order to determine the skeleton, a method of determining a central point of a point cloud data is performed multiple times, each time using different values for one or more starting parameters. The method may yield different central points depending on the selected values for the one or more starting parameters. The resulting plurality of central points is interpreted as the skeleton of the point cloud data.

Abstract: A method may include obtaining a set of events, of a set of pixels of a dynamic vision sensor, associated with an object; determining a set of voltages of the set of pixels, based on the set of events; generating a set of images, based on the set of voltages of the set of pixels; inputting the set of images into a first neural network configured to output a visual motion estimation of the object; inputting the set of images into a second neural network configured to output a confidence score of the visual motion estimation output by the first neural network; obtaining the visual motion estimation of the object and the confidence score of the visual motion estimation of the object, based on inputting the set of images into the first neural network and the second neural network; and providing the visual motion estimation of the object and the confidence score.

Abstract: An object volume acquisition method of an ultrasonic image, for a probe of an ultrasonic system is disclosed.

Abstract: In a method for super resolution imaging, the method includes: receiving, by a processor, a low resolution image; generating, by the processor, an intermediate high resolution image having an improved resolution compared to the low resolution image; generating, by the processor, a final high resolution image based on the intermediate high resolution image and the low resolution image; and transmitting, by the processor, the final high resolution image to a display device for display thereby.

Abstract: The present application discloses a method and an apparatus of obstacle three-dimensional position acquisition for a roadside computing device, and relates to the fields of intelligent transportation, cooperative vehicle infrastructure, and autonomous driving. The method may include: acquiring pixel coordinates of an obstacle in a to-be-processed image; determining coordinates of a bottom surface center point of the obstacle according to the pixel coordinates; acquiring a homography relationship between a ground surface corresponding to the to-be-processed image and a ground surface corresponding to a template image; transforming the coordinates of the bottom surface center point of the obstacle into coordinates on the template image according to the homography relationship; and determining three-dimensional coordinates of the bottom surface center point of the obstacle according to the coordinates obtained by transformation and a ground equation corresponding to the template image.

Abstract: Methods and systems for milling and imaging a sample based on multiple fiducials at different sample depths include forming a first fiducial on a first sample surface at a first sample depth; milling at least a portion of the sample surface to expose a second sample surface at a second sample depth; forming a second fiducial on the second sample surface; and milling at least a portion of the second sample surface to expose a third sample surface including a region of interest (ROI) at a third sample depth. The location of the ROI at the third sample depth relative to the first fiducial may be calculated based on an image of the ROI and the second fiducial as well as relative position between the first fiducial and the second fiducial.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content searching, hosting and/or providing systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods provide an image processing framework that sub-divides computer vision techniques into three computationally efficient steps: detection, classification and matching. These steps provide an improved image processing framework that can analyze live stream data of a media file, in real-time, in order to identify and track specific digital objects depicted therein. This enables not only image processing detection results, but also the capabilities of augmenting the video stream with additional data related to the detected object.

Abstract: A method of video deblurring by an electronic device is described. The processing circuitry of the electronic device acquires N continuous image frames from a video clip the N being a positive integer, and the N continuous image frames including a blurry image frame to be processed. The processing circuitry of the electronic device performs three-dimensional (3D) convolution processing on the N continuous image frames with a generative adversarial network model, to acquire spatio-temporal information corresponding to the blurry image frame.

Abstract: The disclosure provides a data processing method and apparatus, a storage medium and an electronic device. The method includes: performing first processing on data by using a first sub-model corresponding to an artificial intelligence (AI) processing model, to obtain an intermediate processing result, the AI processing model corresponding to the first sub-model and a second sub-model, the first sub-model being generated according to M neural network layers in the AI processing model, the second sub-model being generated according to K neural network layers in the AI processing model, M and K being positive integers greater than or equal to 1; transmitting the intermediate processing result to a first server; and receiving a target processing result from the first server, the target processing result being based on a result of second processing on the intermediate processing result by using the second sub-model.

Abstract: A method and system for matching image features is applied to mine machine vision. The method includes de-noising an image, performing super-pixel segmentation to obtain a plurality of image blocks, calculating the information entropy of each image block to obtain an image block with information entropy greater than a first preset threshold, extracting feature points of the image block, to obtain the feature point set of the image, using a wavelet method to describe the feature points in the feature point set to obtain a feature point descriptor set, and matching feature points in the feature point set with the feature points of a target image.

Abstract: An image processing apparatus is configured to perform processing of detecting an object by using a predetermined number of sample points referred to as particles, the processing including: executing a detection processing configured to calculate a weight for each of the particles, and detect the object by using the calculated weights; and executing a resampling processing configured to assign a particle number to each of the predetermined number of particles, calculate, for each particle, a comparative value by multiplying an average of the weights of the predetermined number of particles by the particle number, calculate, for each particle, a cumulative weight by adding the particle's own weight to the weights of all the particles assigned with the respective particle numbers smaller than the particle's own particle number, and perform a reselection process that executes reselection on the particles of all the particle numbers.

Abstract: Systems and methods for assessing similarity of documents are provided. Embodiments of the systems and methods include extracting a reference document text from a reference document, extracting an archived document text from an archived document, and quantifying the reference document and the archived document. The systems and methods may also include determining a document similarity value of the quantified reference document and the archived document. Determining the document similarity value includes calculating a set of vector similarity values for a set of combinations of a reference document text vector and an archived document text vector, and calculating the document similarity value, including a sum of the plurality of vector similarity values.

Abstract: The present invention relates to an artificial intelligence (AI), which emulates functions of a human brain, such as recognition and reasoning, by utilizing a machine learning algorithm such as deep learning, and relates to context awareness based artificial intelligence application technology for obtaining interest information of a user from an image displayed to the user.

Abstract: A method for determining a position of a tow ball in an image. The method includes obtaining at least one real-time image from a vehicle. The at least one real-time image is processed with a controller on the vehicle to obtain a feature patch (f) describing at least one real-time image. A convolution is performed of the feature patch (f) and each filter (h) from a set of filters (H) with the filter (h) being based on data representative of known tow hitches fixed to the vehicle. A location of a tow ball on the tow hitch is identified in the at least one real-time image is based on the convolution between the feature patch (f) and each filter (h) from the set of filters (H).

Abstract: Methods, systems, devices, and tangible non-transitory computer readable media for determining orientation are provided. The disclosed technology can include capturing images of an environment visible in a field of view of the mobile computing device. Location data associated with a location of the mobile computing device can be received. Image data including information associated with the images can be generated. Based on the image data and one or more machine-learned models, features of one or more objects in the environment can be determined. Based on the location data and the features of the objects, respective orientations of the objects relative to the location of the mobile computing device can be determined. Furthermore, orientation data that includes a geographic orientation of the mobile computing device can be generated based on the respective (geographic) orientations of the objects.