Abstract: Robot positioning is facilitated by obtaining, for each time of a first sampling schedule, a respective indication of a pose of a camera system of a robot relative to a reference coordinate frame, the respective indication of the pose of the camera system being based on a comparison of multiple three-dimensional images of a scene of an environment, the obtaining providing a plurality of indications of poses of the camera system; obtaining, for each time of a second sampling schedule, a respective indication of a pose of the robot, the obtaining providing a plurality of indications of poses of the robot; and determining, using the plurality of indications of poses of the camera system and the plurality of indications of poses of the robot, an indication of the reference coordinate frame and an indication of a reference point of the camera system relative to pose of the robot.

Abstract: A detection method executed by a computer, the detection method includes detecting a plurality of pupil candidates from a face image region in an image of a subject based on specific shape information, and identifying at least one pupil candidate as a pupil from among the plurality of pupil candidates based on brightness information related to an image region outside of the face image region and learning information indicating a relationship between the brightness information and a size of the pupil.

Abstract: An image process apparatus includes an image capture device, a filter, a depth estimation unit, and a mixture unit. The image capture device captures an original image including at least one target object and generates a first depth map corresponding to the original image. The filter selects the at least one target object from the original image according to the first depth map and generates a temporary image including the at least one target object. The temporary image has a depth information of the at least one target object. The depth estimation unit generates a second depth map corresponding to an input image according to the input image. The mixture unit blends the temporary image into a predetermined field depth of the input image to generate a blending image including the input image and the at least one target object according to the depth information and the second depth map.

Abstract: Computer program products for discriminating hand and machine print from each other, and from signatures, are disclosed and include program code readable and/or executable by a processor to: receive an image, determine a color depth of the image; reducing the color depth of non-bi-tonal images to generate a bi-tonal representation of the image; identify a set of one or more graphical line candidates in either the bi-tonal image or the bi-tonal representation, the graphical line candidates including true graphical lines and/or false positives; discriminate any of the true graphical lines from any of the false positives; remove the true graphical lines from the bi-tonal image or the bi-tonal representation without removing the false positives to generate a component map comprising connected components and excluding graphical lines; identify one or more of the connected components in the component map; and output and/or display and indicator of each of the connected components.

Abstract: An image processing apparatus 1 includes a feature point set acquirer, a degree-of-scattering acquirer, a fundamental matrix acquirer and a processor. The feature point set acquirer acquires feature point sets, each including a plurality of feature points within an image. The degree-of-scattering acquirer acquires a degree of scattering indicating a degree of scattered distribution of the feature points. The fundamental matrix acquirer acquires a fundamental matrix, based on coordinates of the feature points p included in feature point sets acquired by the feature point set acquirer and the degree-of-scattering acquired by the degree-of-scattering acquirer, acquires a fundamental matrix indicating the epipolar geometric relationship between the image and another image in a video including the image. The processor performs image processing of the video based on the fundamental matrix acquired by the fundamental matrix acquirer.

Abstract: Methods and systems for determining coordinates for an area of interest on a specimen are provided. One system includes one or more computer subsystems configured for, for an area of interest on a specimen being inspected, identifying one or more targets located closest to the area of interest. The computer subsystem(s) are also configured for aligning one or more images for the one or more targets to a reference for the specimen. The image(s) for the target(s) and an image for the area of interest are acquired by an inspection subsystem during inspection of the specimen. The computer subsystem(s) are further configured for determining an offset between the image(s) for the target(s) and the reference based on results of the aligning and determining modified coordinates of the area of interest based on the offset and coordinates of the area of interest reported by the inspection subsystem.

Abstract: An optical apparatus adapted to contact an object is provided. The optical apparatus includes an optical device and a processing circuit. The optical device includes a reflection structure and a transmission structure. The optical device senses light signals of the object via the reflection structure and the transmission structure. The processing circuit is electrically connected to the optical device. The processing circuit is configured to identify the object according to the light signals. In addition, a method for identifying an object is also provided.

Abstract: Cone Beam Breast CT, (CBBCT) is a three-dimensional breast imaging modality with high soft tissue contrast, high spatial resolution and no tissue overlap. CBBCT-based computer aided diagnosis (CBBCT-CAD) technology is a clinically useful tool for breast cancer detection and diagnosis that will help radiologists to make more efficient and accurate decisions. The CBBCT-CAD is able to: 1) use 3D algorithms for image artifact correction, mass and calcification detection and characterization, duct imaging and segmentation, vessel imaging and segmentation, and breast density measurement, 2) present composite information of the breast including mass and calcifications, duct structure, vascular structure and breast density to the radiologists to aid them in determining the probability of malignancy of a breast lesion.

Abstract: Techniques are disclosed for generating a low-dimensional representation of an image. An image driver receives an image captured by a camera. The image includes features based on pixel values in the image, and each feature describes the image in one or more image regions. The image driver generates, for each of the plurality of features, a feature vector that includes values for that feature corresponding to at least one of the image regions. Each value indicates a degree that the feature is present in the image region. The image driver generates a sample vector from each of the feature vectors. The sample vector includes each of the values included in the generated feature vectors.

Abstract: A system capable of determining which recognition algorithms should be applied to regions of interest within digital representations is presented. A preprocessing module utilizes one or more feature identification algorithms to determine regions of interest based on feature density. The preprocessing modules leverages the feature density signature for each region to determine which of a plurality of diverse recognition modules should operate on the region of interest. A specific embodiment that focuses on structured documents is also presented. Further, the disclosed approach can be enhanced by addition of an object classifier that classifies types of objects found in the regions of interest.

Abstract: An electronic sensor forms a grid to detect surface features of a proximally located object, such as a fingerprint. The grid includes a plurality of parallel drive lines connectable to a drive source and a plurality of parallel pickup lines oriented substantially perpendicular to the drive lines and overlapping the drive lines. The drive lines are separated from the pickup lines by an insulating dielectric layer. The overlaps where the drive lines and pickup lines cross define impedance-sensitive electrode pairs which act as pixels at which surface features of the proximally located object are detected. One or more conductive probes extend from one or more corresponding impedance-sensitive electrode pairs, through an overlay layer of insulating material, to the sensing surface.

Abstract: An invention is disclosed for a real time video analytic processor that embodies algorithms and processing architectures that process a wide variety of sensor images in a fashion that emulates how the human visual path processes and interprets image content. spatial, temporal, and color content of images are analyzed and the salient features of the images determined. These salient features are then compared to the salient features of objects of user interest in order to detect, track, classify, and characterize the activities of the objects. Objects or activities of interest are annotated in the image streams and alerts of critical events are provided to users. Instantiation of the cognitive processing can be accomplished on multi-FPGA and multi-GPU processing hardwares.

Abstract: Apparatuses, methods and storage medium associated with processing an image are disclosed herein. In embodiments, a method for processing one or more images may include generating a plurality of pairs of keypoint features for a pair of images. Each pair of keypoint features may include a keypoint feature from each image. Further, for each pair of keypoint features, corresponding adjoin features may be generated. Additionally, for each pair of keypoint features, whether the adjoin features are similar may be determined. Whether the pair of images have at least one similar object may also be determined, based at least in part on a result of the determination of similarity between the corresponding adjoin features. Other embodiments may be described and claimed.

Abstract: A method for identifying and enumerating candidate target cells within a biological fluid specimen is described. The method includes obtaining a biological fluid specimen, preparing the biological fluid specimen by staining cell features in the biological fluid specimen, capturing a digital image having a plurality of color channels of the biological fluid specimen, and applying image analysis to the digital image. A computer program product for identifying candidate target cells within a biological fluid specimen is also described. The computer program comprises instructions to cause a processor to carry out the image analysis.

Abstract: A system for providing positioning functionality in an apparatus. Apparatuses may comprise various sensor resources and may utilize these resources to sense information at a location. For example, an apparatus may sense visual, signal and/or field information at a location. The apparatus may then compare the sensed information to a mapping database in order to determine position.

Abstract: A method for identify age based on facial features, includes: getting a face image and capturing a face area from the face image; setting a plurality of facial feature points on the face area; defining a plurality of age feature areas on the face area based on coordinates of the plurality of feature points; acquiring age feature from the plurality of age feature area to get an age value; and comparing the age value with at least one threshold value.

Abstract: Various arrangements for determining and setting an authorization level for an unknown person are presented. Facial recognition may be performed on a received video stream. An authorized user may be recognized in the video feed. Additionally, an unknown person may be identified in the video feed. A provisional authorization level may be granted for the unknown person based on proximity between the unknown person and the authorized user in the received video stream.

Abstract: A computer-implemented method for denoising image data includes a computer system receiving an input image comprising noisy image data and denoising the input image using a deep multi-scale network comprising a plurality of multi-scale networks sequentially connected. Each respective multi-scale network performs a denoising process which includes dividing the input image into a plurality of image patches and denoising those image patches over multiple levels of decomposition using a threshold-based denoising process. The threshold-based denoising process denoises each respective image patch using a threshold which is scaled according to an estimation of noise present in the respective image patch. The noising process further comprises the assembly of a denoised image by averaging over the image patches.

Abstract: The present application provides pedestrian detection system and method. A pedestrian detection method includes obtaining an image captured by a camera, and identifying a pedestrian candidate in the image. According to the method, the pedestrian candidate is confirmed by transforming the image into a top view image, calculating the actual height of the pedestrian candidate based on the top view image and extrinsic parameters of the camera, and determining whether the actual height of the pedestrian candidate is within a predetermined pedestrian height range.

Abstract: In some implementations, a computer-implemented method for recognizing facial images may include a multi-stage facial verification process to improve the speed and accuracy of a facial recognition operation. For example, a facial recognition module may include multiple stages where a subset of data is analyzed recursively to improve the speed of the facial recognition processes. The multiple stages may be arranged in a fast-to-slow and coarse-to-fine arrangements such that a match decision may be made at each successive stage.