Abstract: Embodiments of a method and system described herein enable capture of video data streams from multiple, different video data source devices and the processing of the video data streams. The video data streams are merged such that various data protocols can all be processed with the same worker processors on different types of operating systems, which are typically distributed. In an embodiment the multiple video data sources comprises at least one mobile device executing a video sensing application that produces a video data stream for processing by video analysis worker processes. The processes include estimating a queue wait time.

Abstract: An image processing device includes a processor to detect motion of objects in an observation area on the basis of a captured image. The processor also calculates amounts of each detected motion, and calculates a propagation speed, a propagation direction, or both, of the motion for pulsations of the objects.

Abstract: A method for estimating the speed of movement of a first video camera when it captures a current image of a three-dimensional scene, includes storing a reference image corresponding to an image of the same scene captured by a second video camera in a different pose, the reference image including pixels. The method also includes storing the current image, the current image including pixels containing the measurement of a physical quantity measured by that pixel, that physical quantity being the same as the physical quantity measured by the pixels of the reference image. The method further includes storing for each pixel of the reference image or of the current image the measurement of a depth that separates that pixel from the point of the scene photographed by that pixel, estimating the pose of the first camera, and estimating the speed of movement of the first camera.

Abstract: A system for estimating a pose of one or more persons in a scene includes a camera configured to capture an image of the scene; and a data processor configured to execute computer executable instructions for: (i) receiving the image of the scene from the camera; (ii) extracting features from the image of the scene for providing inputs to a keypoint subnet and a person detection subnet; (iii) generating one or more keypoints using the keypoint subnet; (iv) generating one or more person instances using the person detection subnet; (v) assigning the one or more keypoints to the one or more person instances by learning pose structures from the image data; and (vi) determining one or more poses of the one or more persons in the scene using the assignment of the one or more keypoints to the one or more person instances.

Abstract: Apparatuses, systems and methods are provided for determining vehicle driver distractions. More particularly, apparatuses, systems and methods are provided for determining distractions at particular geographic locations.

Abstract: Techniques for object re-identification based on temporal context. Embodiments extract, from a first image corresponding to a first camera device and a second image corresponding to a second camera device, a first plurality of patch descriptors and a second plurality of patch descriptors, respectively. A measure of visual similarity between the first image and the second image is computed, based on the first plurality of patch descriptors and the second plurality of patch descriptors. A temporal cost between the first image and the second image is computed, based on a first timestamp at which the first image was captured and a second timestamp at which the second image was captured. The measure of visual similarity and the temporal cost are combined into a single cost function, and embodiments determine whether the first image and the second image depict a common object, using the single cost function.

Abstract: Embodiments disclosed herein provide systems and methods for determining motion of a striking or blocking device. Embodiments may be utilized in various embodiments when it is desired to track, determine, etc. the motion of a device. For example, embodiments may be utilized in martial arts, sports, activities, instructional videos, video games, etc. More specifically, embodiments may be configured to automatically detect fast movements of a device using video cameras or image capturing devices.

Abstract: Embodiments of a method and system described herein enable capture of video data streams from multiple, different video data source devices and the processing of the video data streams. The video data streams are merged such that various data protocols can all be processed with the same worker processors on different types of operating systems, which are typically distributed. In an embodiment the multiple video data sources comprises at least one mobile device executing a video sensing application that produces a video data stream for processing by video analysis worker processes. The processes include automatically detecting features in an urban scene comprising building entrances.

Abstract: Body joint tracking is applied in various industries and medical field. In body joint tracking, marker less devices plays an important role. However, the marker less devices are facing some challenges in providing optimal tracking due to occlusion, ambiguity, lighting conditions, dynamic objects etc. System and method of the present disclosure provides an optimized body joint tracking. Here, motion data pertaining to a first set of motion frames from a motion sensor are received. Further, the motion data are processed to obtain a plurality of 3 dimensional cylindrical models. Here, every cylindrical model among the plurality of 3 dimensional cylindrical model represents a body segment. The coefficients associated with the plurality of 3 dimensional cylindrical models are initialized to obtain a set of initialized cylindrical models. A set of dynamic coefficients associated with the initialized cylindrical models are utilized to track joint motion trajectories of a set of subsequent frames.

Abstract: A method and a device for measuring the topography and/or the gradients and/or the curvature of an optically active surface of an object are disclosed. The device allows the object to be arranged in a receiving region with a contact surface for contact with the object. Inside the device, there is a plurality of point light sources that provide light that is reflected at the surface to be measured of an object arranged in the receiving region. The device includes at least one camera with an objective assembly and an image sensor for detecting a brightness distribution which is produced on a light sensor by the light of the point light sources reflected at the surface to be measured.

Abstract: According to one embodiment, an MRI apparatus includes a data acquisition unit and an image generation unit. The data acquisition unit acquires MR data from an object. The MR data correspond to a sampling region asymmetric in a wave number direction in a k-space. The image generation unit generates amplitude image data, in a real space, based on first k-space data after zero padding to a non-sampling region of the MR data and generates MR image data by data processing of the amplitude image data or convolution processing of the amplitude image data. The data processing converts the amplitude image data into second k-space data, performs filtering of the second k-space data and converts the second k-space data after the filtering into real space data. The convolution processing uses a function in the real space. The function is derived by converting a window function for the filtering.

Abstract: Embodiments and processes of computer tomography perform tasks associated with denoising a reconstructed image using an anisotropic diffusion filter and adaptively weighting an iterative instance of the diffused image based upon the product of a weight value and a difference between the iterative instance of the diffused image and the original image. In general, the adaptive weighting is a negative feedback in the iterative steps.

Abstract: A method and system is provided for planogram compliance check based on visual analysis. The present method and system comprises acquiring a product shelf image, identifying a region of interest (ROI) from the at least one product shelf image, extracting a perspective distortion rectification of the identified ROI to generate a rectified shelf image, applying Hausdroff distance based image map for occupancy estimation in shelf images extracting one or more rows from the rectified shelf image wherein the rectified shelf image comprises a plurality of horizontal row partitions, and deriving a product count and placement information for each of the extracted one or more rows based on the extracted rows and the occupancy estimation.

Abstract: A motion display system includes: a detector that detects an acceleration of a body part of a test subject; an imager that generates a moving image by imaging a motion of the test subject; an identifier that is attached to the test subject to determine a position of the body part within the moving image; a superimposer that superimposes a motion trajectory of the body part generated based on the acceleration detected by the detector on a position of the body part determined based on the identifier within the moving image generated by the imager in synchronization with the moving image; and a display that displays the moving image on which the motion trajectory is superimposed by the superimposer.

Abstract: A method and system are provided for characterizing a portion of biological tissue. This invention comprises a smartphone and tablet deployable mobile medical application that uses device sensors, internet connectivity and cloud-based image processing to document and analyze physiological characteristics of hand arthritis. The application facilitates image capture and performs image processing that identifies hand fiduciary features and measures hand anatomical features to report and quantify the progress of arthritic disease.

Abstract: A system generates a user hand shape model from a single depth camera. The system includes the single depth camera and a hand tracking unit. The single depth camera generates single depth image data of a user's hand. The hand tracking unit applies the single depth image data to a neural network model to generate heat maps indicating locations of hand features. The locations of hand features are used to generate a user hand shape model customized to the size and shape of the user's hand. The user hand shape model is defined by a set of principle component hand shapes defining a hand shape variation space. The limited number of principle component hand shape models reduces determination of user hand shape to a smaller number of variables, and thus provides for a fast calibration of the user hand shape model.

Abstract: This Invention is directed at the automated analysis of body scanner images. Body scanners are used in airports and other secured facilities to detect weapons, explosives, and other security threats hidden under persons' clothing. These devices use x-rays, millimeter waves and other radiant energy to produce an electronic image of the person's body and any concealed objects. Examination of these images by human analysts is slow, expensive, and subject to privacy concerns. The Invention provides automated analysis of body scanner images by recognizing that human anatomy is bilaterally symmetric to a high degree, while concealed objects are asymmetric. Digital techniques are used to separate the scanned image into its symmetric and asymmetric parts, thereby effectively separating anatomic from non-anatomic image features.

Abstract: A method for image matching includes acquiring a template image and a target image; acquiring a group of template features according to the template image; extracting a group of target features according to the target image; and according to template features and target features, calculating an degree of image similarity between the template image and each frame of target images, and using a target image with the maximum degree of image similarity as a matched image to the template image. In the image-matching method, image matching is performed by calculating an degree of image similarity between a template image and each target image according to a degree of image similarity between template features and target features, so that non-redundancy of features in an image matching process and correct image matching can be guaranteed, and the image matching accuracy can be improved.

Abstract: A method and system for correlating slice profiles associated with a series of magnetic resonance images taken at a plurality of positions. The method comprises first positioning a patient in a first position in the imaging volume of the magnet. A scout scan is then acquired. Selection is then made of an anatomical landmark in the scout scan, which will be referred to as an anatomical fiducial. A particular slice, typically one of a stack of slices to be acquired in a subsequent scan, is selected and precisely positioned at the location of the anatomical fiducial in the scout scan. Following completion of the scan, the patient may be repositioned, necessitating a new scout scan to set up parameters for a second scan.

Abstract: A phase deviation method determines an offset between a reference and suspect signal by analyzing a phase deviation surface created by computing a deviation metric for phase shift and then analyzing a surface formed from the deviation metrics for an array of offsets. The phase deviation method analyzes the deviation surface to determine an offset that minimizes phase deviation. This method is applied at increasing levels of detail to refine the determination of the offset.