A virtual reality system is provided. The virtual reality system includes a host device and a head mounted display apparatus to be worn by a user. The head mounted display apparatus includes a first wireless module, a second wireless module, a multimedia module, a multi-sensing module, and a peripheral hub. The multimedia module receives multimedia content from the host device through the first wireless module. The multi-sensing module obtains sensing information regarding the head mounted display apparatus and the user. The peripheral hub receives communication data from the host device through the second wireless module, and provides the sensing information to the host device through the second wireless module.

A method and non-transitory computer-readable medium capture an image of bulk grain and apply a feature extractor to the image to determine a feature of the bulk grain in the image. For each of a plurality of different sampling locations in the image, based upon the feature of the bulk grain at the sampling location, a determination is made regarding a classification score for the presence of a classification of material at the sampling location. A quality of the bulk grain of the image is determined based upon an aggregation of the classification scores for the presence of the classification of material at the sampling locations.

Selected image data or specific information thereon is stored in association with moving image data as a management marker of a selected image. The selected image data is selected from among still image data extracted from the moving image data. When an output image of the selected image is captured, image analysis is performed on the captured image data to acquire a management marker of a captured image. A management marker of a selected image corresponding to the management marker of the captured image from among management markers of selected images stored in the storage is specified. Digest moving image data is generated by picking out a part of moving image data associated with the specific management marker. Control is performed so that a digest moving image is playbacked and displayed on the display section.

A computer-implementable method of analyzing tissues of a retina. A polarization-sensitive (PS-OCT) image data set of the retina is received from a polarization-sensitive device, each element in the polarization-sensitive image data set being associated with an intensity value ({I.sub.1, . . . , I.sub.L}) and a polarization direction ({P.sub.1, . . . , P.sub.L}). A likelihood score is determined for each element of the polarization-sensitive image data set based on the intensity value of the element and a degree of divergence (μ*.sup.TP or D.sub.2) of the polarization direction associated with the element from a reference polarization direction (μ*) associated with the polarization sensitive image data set, wherein the likelihood score indicates whether said element is drawn from a directionally polarized distribution or a depolarizing distribution, Elements of the polarization-sensitive image data set are classified using the determined likelihood scores to analyze tissues of the retina.

Disclosed is a novel system, and method for matching a spent firearm cartridge. The method starts with applying a directed self-assembly (DSA) process to produce a nano-scale pattern on a tip of a firing pin for a firearm. The DSA process including: a) disposing a neutral substrate on the firing pin; b) lithographically placing two or more base polymer chains on the neutral substrate, at least two of the two or more base polymer chains being different lengths, so that the two or more base polymer chains align end-to-end in an alternating structure, and c) extracting at least one of the two or more base polymer chains leaving at least one of the base polymer chains remaining thereby forming a randomly oriented pattern. Next, the randomly oriented pattern is used as blocking mask to form a randomly oriented metallization pattern.

Method for locating anomalous features in medical images in which medical images are supplied by an external source. A sequence of specific measurements is executed on the supplied data to obtain image-related metrics. The metrics are compared to corresponding values in a database resulting in an anomalous/not anomalous determination. Anomalous determinations are presented to the test operator for analysis along with supplemental historical data. In application to all types of medical imagery, potential anomalies are located resulting in an efficient and accurate diagnosis. For paired body parts having symmetrical properties, as a pre-screening stage, a line of symmetry between the body parts is determined and symmetric regions of the two body parts on opposite sides of the determined line of symmetry are analyzed for differences. The metric comparison using the database is performed between both symmetric regions only when differences between the symmetric regions of the subject medical image are present.

An improved system and method for digital image classification is provided. A host computer having a processor is coupled to a memory storing thereon reference feature data. A graphics processing unit (GPU) having a processor is coupled to the host computer and is configured to obtain, from the host computer, feature data corresponding to the digital image; to access, from the memory, the one or more reference feature data; and to determine a semi-metric distance based on a Poisson-Binomial distribution between the feature data and the one or more reference feature data. The host computer is configured to classify the digital image using the determined semimetric distance.

A method for estimating a plurality of camera, comprising using at least one processor executing a code for: extracting a plurality of image features of a plurality of landmarks from a plurality of images captured by at least one camera from at least one pose, the plurality of landmarks calibrated with respect to a certain coordinate system; identifying among the plurality of image features at least one image feature documented in at least some of the images; producing scale values of at least one common image feature by analyzing the at least some of the images; determining a plurality of estimated poses of the at least one camera with respect to the certain coordinate system by using the scale values in calculating a minimal re-projection error between the plurality of image features and a plurality of predicted image features; and outputting the plurality of estimated poses.

What is disclosed is a system and method for automatically segmenting a breast from surrounding tissue in a thermal image. A thermal image of at least one breast of the patient is received. The thermal image is then analyzed to identify a set of N points around the breast, a contour of an outline of the body, and isotherms of the axilla and infra-mammary fold. Thereafter, the points are connected together to form a N-sided irregular polygon which segments the breast from surrounding tissue. Each of the points is a vertex of the polygon and comprises a draggable object which enables a user to selectively manipulate a shape of the polygon. A user can add/delete vertices from the polygon as desired. The area of the image encompassed by the polygon is communicated to a breast cancer screening algorithm performing automated or semi-automated screening.

Systems and methods for training a recursive neural network (RNN) is provided. The method includes generating, by the processor using the RNN, a plurality of embedding vectors based on a plurality of observations, wherein the observations include (i) a subject, (ii) an action taken by the subject, and (iii) an object on which the subject is taking the action on, wherein the subject and object are constant. The method further includes generating, by the processor, predictions of one or more future events based on one or more comparisons of at least some of the plurality of embedding vectors. The method also includes initiating, by the processor, based on the predictions, an action to a hardware device to mitigate expected harm to at least one item selected from the group consisting of the hardware device, another hardware device related to the hardware device, and a person related to the hardware device.