Abstract: According to one embodiment, an image analysis device includes one or more processors configured to receive input of an image; calculate feature amount information indicating a feature of a region of the image; recognize a known object from the image on the basis of the feature amount information, the known object being registered in learning data of image recognition; recognize a generalization object from the image on the basis of the feature amount information, the generalization object being generalizable from the known object; and output output information on an object identified from the image as the known object or the generalization object.

Abstract: A pet monitoring method and a pet monitoring system according to embodiments of the disclosure are provided. The method is described hereinafter. An image is obtained by a photographic device. At least one of an exercise status detection, an excretion status detection and a danger status detection of a pet is performed according to the image. Pet management information is presented on a management interface of a remote device according to a detection result.

Abstract: An automatic threat recognition (ATR) system is disclosed for scanning an article to recognize contraband items or items of interest contained within the article. The ATR system uses a CAT scanner to obtain a CT image scan of objects within the article, representing a plurality of 2D image slices of the article and its contents. Each 2D image slice includes information forming a plurality of voxels. The ATR system includes a computer and determines which voxels have a likelihood of representing materials of interest. It then aggregates those voxels to produce detected objects. The detected objects are further classified as items of interest vs. not of interest. The ATR system is based on learned parameters for a novel interaction of global and object context mechanisms. ATR system performance may be optimized by using jointly optimal global and object context parameters learned during training. The global context parameters may apply to the article as a whole and facilitate object detection.

Abstract: A video analysis system includes: a video data acquiring means that acquires video data; a moving object detecting means that detects a moving object from video data acquired by the video data acquiring means, by using a moving object detection parameter, which is a parameter for detecting a moving object; an environment information collecting means that collects environment information representing an external environment of a place where the video data acquiring means is installed; and a parameter changing means that changes the moving object detection parameter used when the moving object detecting means detects a moving object, on the basis of the environment information collected by the environment information collecting means.

Abstract: An image processing device 10 includes: a segmentation unit 21 that segments an input image 200 representing a result of observing an ocean surface region and a land surface region from overhead into ocean surface block images 211 and land surface block images 212, based on a segmentation criterion 210; a first determination unit 22 that determines a binarization criterion 220 for the ocean surface block images 211, based on a scattering model for electromagnetic waves in the ocean surface region; a second determination unit 23 that determines a binarization criterion 230 for the land surface block images 212, based on the binarization criterion 220 and a positional relationship between the ocean surface block images and the land surface block images; and a generation unit 25 that generates a land mask image 250 by performing binarization processing on the input image 200 based on the binarization criterion 220 and the binarization criterion 230.

Abstract: Present embodiments pertain to systems, apparatuses, and methods for analyzing and reporting rotational or reciprocating movements in mechanical structures, machines, and machine components, including measuring the speed of rotation or reciprocation of a component on the structure, through the use of an acquired video recording representing a plurality of cycles of motion, by measuring intensity values of a subset of pixels contained in a region of interest within the video recording in a plurality of frames of the video recording, thereby determining distance per time period of rotational or reciprocal motion of a machine or machine component, and the application of numerical algorithm to the repeating patterns in the intensity waveform enables the determination of the average speed value or with the use of a gear wheel or graduated tape, instantaneous values for speed can be derived and the torsional vibration characteristics of the component determined.

Abstract: A method of generating a template image includes: receiving an input from a user representing identifications of an object in different respective slices of a volumetric image; using the input to determine a volume-of-interest (VOI) that includes voxels in a subset of the volumetric image; and determining the template image using at least some of the voxels in the VOI, wherein the act of determining the template image comprises performing a forward projection of the at least some of the voxels in the VOI using a processor. An image processing method includes: obtaining a volumetric image; performing forward projection of voxels in the volumetric image from different positions onto a first plane using a processor; and summing projections on the first plane resulted from the forward projection from the different positions to create a first image slice in the first plane.

Abstract: Provided is a data generation apparatus including an image reader configured to extract image recognition data by performing image recognition for identifying face, posture, and multitasking of a user viewing an image, and transmit the image recognition data to a score processing unit; the score processing unit configured to apply an additional or deduction point according to a preset conditional value of the additional and deduction point for immersion determination to the image recognition data extracted from the image reader and convert an immersion determination value to a numerical value; an immersion determinator configured to determine an immersion state for each time section based on a preset criterion with respect to the immersion determination value converted by the score processing unit; and a combined data generator configured to combine a user identification (ID), viewing channel information, time information, and an immersion state and generate the same as a data set.

Abstract: A method of aligning two 3D digital representations of at least a part of each of the upper and lower jaw of a patient, the method including segmenting the 3D digital representations to determine the shape and position of each of the patient's teeth in each of the 3D digital representations; and using a set of known anatomical concepts to constrain the fit of the two 3D digital representations to get a preliminary fit.

Abstract: The present invention provides a processing apparatus including: an image analysis unit configured to extract a plurality of types of feature values of a person detected from an image; a registration management unit configured to determine whether or not data of the detected person is stored in a storage unit in which the feature value of each of a plurality of persons is stored on the basis of the extracted feature value; a change determination unit configured to determine whether or not there is a change in appearance of the detected person on the basis of the feature value stored in the storage unit and the extracted feature value in a case where it is determined that the data of the detected person is stored; and a notification unit configured to give notice of a person determined to have a change in appearance.

Abstract: A computer system selects a kernel and kernel parameters for a first Support Vector Machine (SVM) model, testing the SVM model on a feature matrix T of n feature vectors of length m to produce false positive (FP) data set and false negative (FN) data set by a computer processor, wherein n and m are integer numbers, copies the feature matrix T to produce a feature matrix T_best, and checking if a ratio (T_best sample number)/(SVM support vector number) is above a threshold for the SVM model on T_best. If the ratio is above the threshold, SVM predictions are performed using the SVM model on the feature matrix T_best. The first SVM model can be used classify the faces or the objects in the images. An image-product design can be created based on the faces or the objects in the images classified by the first SVM model using the feature matrix T_best.

Abstract: A pedestrian re-identification method includes: obtaining a target video containing a target pedestrian and at least one candidate video; encoding each target video segment in the target video and each candidate video segment in the at least one candidate segment separately; determining a score of similarity between the each target video segment and the each candidate video segment according to encoding results, the score of similarity being used for representing a degree of similarity between pedestrian features in the target video segment and the candidate video segment; and performing pedestrian re-identification on the at least one candidate video according to the score of similarity.

Abstract: A computer-implemented method and system provide the ability to determine and provide a safety risk analysis for construction. Construction related data is obtained and includes textual data and a visual artifact for the construction project. A construction safety context is identified based on the construction related data. Based on the construction safety context, a safety participant risk score that assigns a numerical safety risk participant value to any entity involved in the construction project is determined. Based on the safety risk participant score, a safety project score that assigns a risk level on a per-project basis is determined. The safety risk analysis is presented based on the safety participant risk score and safety project score, via a graphical user interface.

Abstract: A gas-detection image processing device includes first, second, and third processors. The first processor generates a plurality of first images by applying processing to extract a gas candidate region to each of a plurality of infrared images captured in time series during a predetermined period. The second processor generates a second image, while using the first images, by applying processing to extract an appearance region indicating that a gas candidate region has appeared in at least a part of the predetermined period. The second processor generates two or more second images by applying the processing to extract the appearance region to the first images generated in a manner corresponding to two or more of the predetermined periods respectively. The third processor generates a third image by applying processing to extract a common region of the appearance regions while using the two or more of the second images.

Abstract: An apparatus and method for detecting a fake fingerprint is disclosed. The apparatus may divide an input fingerprint image into blocks, determine an image quality assessment (IQA) value associated with each block, determine a confidence value based on the IQA values using a confidence determination model, and determine whether an input fingerprint in the input fingerprint image is a fake fingerprint based on the determined confidence value.

Abstract: The APPARATUSES, METHODS AND SYSTEMS FOR A VIDEO REMOTE DEPOSIT CAPTURE PLATFORM (hereinafter “RDC-Video”) provides a platform for remote deposit by obtaining images of a check from streaming video captured by a video camera, wherein the RDC-Video transforms captured check images and/or entered check deposit information inputs via RDC-Video components into deposit confirmation outputs. For example, in one embodiment, a user may employ a personal computer connected to a web camera, and/or a smartphone with a built-in camera to initiate the remote deposit by holding a check in front of the camera, and the RDC-Video may capture images of the check and send them to a financial institution for deposit processing.

Abstract: Provided is a non-transitory computer-readable medium storing instructions for performing image correction by determining a plurality of first facial feature points of a first face included in a first image, displaying (i) at least a portion of the plurality of first facial feature points and (ii) the first image on a screen of an electronic device, recognizing a first input from an external source for moving at least one first facial feature point among the plurality of first facial feature points in the first image displayed on the screen, generating a corrected first image by moving the at least one first facial feature point in response to the first input and correcting the first image based on the moved at least one first facial feature point, and generating correction pattern information by analyzing a correction pattern of the first image.

Abstract: Guided restoration is used to restore video data degraded from a video frame. The video frame is divided into restoration units (RUs) which each correspond to one or more blocks of the video frame. Restoration schemes are selected for each RU. The restoration schemes may indicate to use one of a plurality of neural networks trained for the guided restoration. Alternatively, the restoration schemes may indicate to use a neural network and a filter-based restoration tool. The video frame is then restored by processing each RU according to the respective selected restoration scheme. During encoding, the restored video frame is encoded to an output bitstream, and the use of the selected restoration schemes may be signaled within the output bitstream. During decoding, the restored video frame is output to an output video stream.

Abstract: A system for component inspection comprising at least one sensor configured to capture sensor data of the component; and a processor coupled to the at least one sensor, the processor comprising at least one model configured to separate the sensor data into a normal category and an abnormal category.

Abstract: Subject matter disclosed herein may relate to systems, devices, and/or processes for processing signals and/or states representative of behavioral and/or biological state.