Abstract: An image processing method and a device configured to implement the same are disclosed. The method comprises: obtaining optical input from a hybrid imaging device, wherein an obtained optical input comprises a first component and a second component that temporally corresponds to the first component; wherein the first component of the obtained optical input corresponds to a first temporal resolution, while the second component of the obtained optical input corresponds to a second temporal resolution higher than that of the first component; performing image restoration operation on a first subset of the first component of the obtained optical input in accordance with data from the second component of the obtained optical input; and performing image fusion operation to generate fused image data from an output of the image restoration operation and a second subset of the first component of the obtained optical input.

Abstract: Methods and systems for identifying areas of interest in an image and management of images are disclosed. To manage identification of areas of interest in an image, subject matter expert driven processes may be used to identify the areas of interest. The identified areas of interest may be used to establish plans to guide subsequent use of the image. The identified areas of interest may also be used to establish plans to cache portions of the image to speed subsequent use of the image.

Abstract: A method, computer system, and a computer program product for historical image search is provided. The present invention may include receiving an image search criteria. The present invention may also include generating a composite image search query based on the received image search criteria. The present invention may further include searching for a matching historical image based on the generated composite image search query. The present invention may also include returning a historical image search result.

Abstract: A method of determining a target of a subject's gaze from an image of the subject within a scene is disclosed. The method comprises analyzing the image and determining information associated with the image. A processor configured to analyze the image and determine information associated with the image is also disclosed. Finally, a non-transitory computer readable storage device comprising computer executable instructions for determining a target of a subject's gaze is disclosed.

Abstract: The present application provides an image processing method, an image processing device, a computer storage medium and a terminal, the image processing method includes: determining convolution kernels of at least two sizes for feature extraction; performing sparsity constraint for the determined convolution kernels of at least two sizes for feature extraction through a preset objective function; and performing feature extraction on an image based on the convolution kernels subjected to the sparsity constraint.

Abstract: Methods, non-transitory computer readable media, tracker devices, central processor devices, and optical tracking systems that facilitate improved optical tracking in surgical environments are disclosed. With this technology, background images are captured within an acquisition sequence. The background images are used to analyze the quality of current images that are captured in the acquisition sequence and to determine an angular position of optical sensor modules of optical tracker devices with respect to light sources coupled to a reference frame that can be integral with an opposing one of the tracker devices. Using multiple tracking devices facilitates a reciprocal angular position determination that is more accurate and can withstand occlusion of an optical sensor module.

Abstract: Provided are a pedestrian search method, a server, and a storage medium. The pedestrian search method is described as follows: a pedestrian detection is performed on each segment of monitoring video to obtain multiple pedestrian tracks, where each pedestrian track of the multiple pedestrian tracks includes multiple video frame images of a same pedestrian; and pedestrian tracks belonging to the same pedestrian is determined according to video frame images in the multiple pedestrian tracks, and the pedestrian tracks of the same pedestrian are merged.

Abstract: A system, method, and apparatus for displaying a fused reconstructed image with a multidimensional image are disclosed. An example imaging system receives a selection corresponding to a portion of a displayed multidimensional visualization of a surgical site. At the selected portion of the multidimensional visualization, the imaging system displays a portion of a three-dimensional image which corresponds to the selected multidimensional visualization such that the displayed portion of the at least one of the three-dimensional image or model is fused with the displayed multidimensional visualization.

Abstract: A method includes detecting a first object in a first area of a scene; determining, based on characteristics of the first object, a first probability value indicating a first probability that the detected first object; detecting a second object in a second area of the scene captured in a second stream of image frames by a second camera of the camera system different from the first camera, wherein the second area at least partly overlaps the first area; determining, based on characteristics of the second object, a second probability value indicating a second probability that the detected second object; and when the second probability value is below a second threshold value and the first probability value is above a first threshold value determining an updated second probability value by increasing the second probability value.

Abstract: An example computing platform comprising is configured to (i) receive, via one or more cameras positioned on a construction site, a plurality of images, (ii) detect, within the plurality of images, a plurality of objects being worn by respective workers on the construction site, (iii) select, from the plurality of images, a set of images depicting a particular worker, and (iv) based on the selected set of images depicting the particular worker, determine a plurality of trade probabilities for the particular worker, each trade probability in the plurality of trade probabilities indicating a likelihood that the particular worker belongs to a particular trade from among a plurality of trades.

Abstract: A system includes an imaging system and a fiber detection and alignment system. The fiber detection and alignment system includes one or more neural networks trained to detect end faces of one or more fibers in an image and to predict rotation angle and direction of rotation for each fiber that will align an axis of the fiber to associated reference keys. In operation, the imaging system generates an image of an end face of one or more polarization-maintaining (PM) fibers to be aligned. The fiber detection and alignment system generates fiber detection information, such as bounding boxes around end faces of each fiber in the image, and fiber alignment information, such as an alignment instruction indicating a rotation angle and direction of rotation that will align fast or slow axes of each fiber to associated reference keys. The novel system provides a scalable technique to automatically align PM fiber.

Abstract: An information processing apparatus (10) includes a time and space information acquisition unit (110) that acquires high-risk time and space information indicating a spatial region with an increased possibility of an accident occurring or of a crime being committed and a corresponding time slot, a possible surveillance target acquisition unit (120) that identifies a video to be analyzed from among a plurality of videos generated by capturing an image of each of a plurality of places, on the basis of the high-risk time and space information, and analyzes the identified video to acquire information of a possible surveillance target, and a target time and space identification unit (130) that identifies at least one of a spatial region where surveillance is to be conducted which is at least a portion of the spatial region or a time slot when surveillance is to be conducted, from among the spatial region and the time slot indicated by the high-risk time and space information, on the basis of the information of the

Abstract: Disclosed herein is a method for supporting an attention test based on an attention map and an attention movement map. The method includes generating a score distribution for each segment area of frames satisfying preset conditions, among frames of video content (video) that is produced in advance so as to be suitable for the purpose of a test, generating an attention map corresponding to the frames based on the distribution of the gaze point of a subject, generating an attention movement map corresponding to the frames based on information about movement of the gaze point of the subject, and calculating the attention of the subject using the score distribution for each segment area, the attention map, and the attention movement map.

Abstract: A technique for synthesizing a shape includes generating a first plurality of offset tokens based on a first shape code and a first plurality of position tokens, wherein the first shape code represents a variation of a canonical shape, and wherein the first plurality of position tokens represent a first plurality of positions on the canonical shape. The technique also includes generating a first plurality of offsets associated with the first plurality of positions on the canonical shape based on the first plurality of offset tokens. The technique further includes generating the shape based on the first plurality of offsets and the first plurality of positions.

Abstract: A system, method, and computer program for updating calibration lookup tables within an autonomous vehicle or transmitting roadway marking changes between online and offline mapping files is disclosed. A LIDAR sensor may be used for generating an online (rasterized) mapping file with online intensity values which are compared against a correlated offline (rasterized) mapping file having offline intensity values. The online intensity value may be used to acquire a lookup table having a normal distribution that is compared against the offline intensity value. The lookup table may be updated when the offline intensity value is within the normal distribution. Or the vehicle may transmit a roadway marking change when the offline intensity value is outside the normal distribution.

Abstract: A computer application may aim to identify first and second “matching” objects. The matching method cannot necessarily be based on how visually similar the two objects are to each other because two matching objects might be different and/or be visually different. Moreover, the images of the objects to be matched might not necessarily have metadata to assist in the matching. In some embodiments, a machine learning model may be trained using a set of digital images, each including two or more matching objects. Triplet loss training may be used, and each triplet may include: an image of a first object extracted from a first image, an image of an object that is visually similar to an image of a second object extracted from the first image, and an image of a third object extracted from a different image.

Abstract: An information processing apparatus (10) includes a time and space information acquisition unit (110) that acquires high-risk time and space information indicating a spatial region with an increased possibility of an accident occurring or of a crime being committed and a corresponding time slot, a possible surveillance target acquisition unit (120) that identifies a video to be analyzed from among a plurality of videos generated by capturing an image of each of a plurality of places, on the basis of the high-risk time and space information, and analyzes the identified video to acquire information of a possible surveillance target, and a target time and space identification unit (130) that identifies at least one of a spatial region where surveillance is to be conducted which is at least a portion of the spatial region or a time slot when surveillance is to be conducted, from among the spatial region and the time slot indicated by the high-risk time and space information, on the basis of the information of the

Abstract: Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are commonly used to assess patients with known or suspected pathologies of the lungs and liver. In particular, identification and quantification of possibly malignant regions identified in these high-resolution images is essential for accurate and timely diagnosis. However, careful quantitative assessment of lung and liver lesions is tedious and time consuming. This disclosure describes an automated end-to-end pipeline for accurate lesion detection and segmentation.

Abstract: A method at a computing device for classifying elements within an input, the method including breaking the input into a plurality of patches; for each patch: creating a vector output; applying a characterization map to select a classification bin from a plurality of classification bins; and utilizing the selected classification bin to classify the vector output to create a classified output; and compiling the classified output from each patch.

Abstract: Disclosed herein is digital object generator that makes uses a one-way function to generate unique digital objects based on the user specific input. Features of the input are first extracted via a few-shot convolutional neural network model, then evaluated weight and integrated fit. The resulting digital object includes a user decipherable output such as a visual representation, an audio representation, or a multimedia representation that includes recognizable elements from the user specific input.