Abstract: A method and a system for analyzing a target in a stereo image by displaying the stereo image using a cascade structure are disclosed. The method includes for the input stereo image, generating, based on a first relevant feature, rule or model of the stereo image, at least a first first-level structure map, each of the first first-level structure maps being generated based on an individual tolerance level of the first relevant feature, rule or model, and each of the first first-level structure maps including the target at an individual first division level; and at least partly integrating the first first-level structure maps and analyzing the target in the stereo image, to obtain a structure map of a first-level target analysis result including the target.

Abstract: Retinal vessel extraction on color images of eyes are disclosed. In one embodiment, the method comprises performing alpha matting on a multi-dimensional feature set derived from image data of a first image and performing retinal vessel extraction, including performing segmentation on the image by separating foreground and background image data from the first image using an output from the alpha matting.

Abstract: A method for analyzing related images corresponding system and vehicle including such system as well as a computer program product for executing the method. The method comprises obtaining at least a first and a second image, defining a pixel patch in the first image for which a correlation shall be calculated, calculating matching cost values between each pixel of the pixel patch in the first image and its corresponding pixel in each of a plurality of pixel patches in the second image, wherein the pixel patches in the second image differ in position in the second image and include the pixel patch with a target position, aggregating the matching cost values of those corresponding pixels of all patches in the second image which match best to generate an aggregation window associated with the target position, and producing a signal including information on the target position.

Abstract: Methods for detecting and analyzing individual nanoparticles of the same, similar, or different sizes co-existing in a fluid sample using multi-spectral analysis are disclosed. A plurality of light sources may be configured to produce a plurality of light beams at different spectral wavebands. An optical assembly may be configured to combine the plurality of light beams into one or more incident light sheets. Each incident light sheet may illuminate one or more nanoparticles in a liquid sample. One or more image detectors may be configured to detect, using a plurality of wavelengths, light scattered or emitted by one or more nanoparticles. The plurality of wavelengths may correspond to the different spectral wavebands of the plurality of light beams. Related apparatus, systems, techniques, and articles are also described.

Abstract: The disclosed technology automatically (e.g., programmatically) initializes predictive information for tracking a complex control object (e.g., hand, hand and tool combination, robot end effector) based upon information about characteristics of the object determined from sets of collected observed information. Automated initialization techniques obviate the need for special and often bizarre start-up rituals (place your hands on the screen at the places indicated during a full moon, and so forth) required by conventional techniques. In implementations, systems can refine initial predictive information to reflect an observed condition based on comparison of the observed with an analysis of sets of collected observed information.

Abstract: A position detection device obtains image coordinate groups representing a coordinate of a target object in each acquired image having first and second acquired image groups. The first acquired image group has acquired images obtained at an image acquiring timing in a reference period. The second acquired image group has acquired images obtained at an image acquiring timing in the reference period, which is delayed from the image acquiring timing of the first acquired image group by an asynchronous time. The device performs a Fourier transformation of each of a first locus and a second locus, and calculates a first frequency waveform based on the first locus and a second frequency waveform based on the second locus. The device calculates a position of the target object based on a relationship in which the frequency waveforms are delayed relative to each other by a phase corresponding to the asynchronous time.

Abstract: A method for determining a distance between two spatial points, thus between a first point and a second point, includes recording a first picture from a first viewing point, wherein the first picture includes a reference object and the first point, recording a second picture for a second viewing point, wherein the second picture includes the reference object and the second point and wherein the second viewing point is different than the first viewing point and finally determining the distance between the first point and the second point from picture data of the first picture and picture data of the second picture using a known dimension of the reference object. Thereby, the first point and/or the second point can be arranged outside a plane encompassing the reference object.

Abstract: An image processing apparatus and method take as input a pre-op reference image (OP) and a stream (A) of angiographic images (A1-A3). Based on multiple pre-defined regions of interest (ROIa-c) in the pre-op reference image (PO), the angiographic image best showing when displayed a respective one of the regions of interest (ROIa-c) is detected from among the stream (A) of angiographic images (A1-A3). The detected angiographic image is associated with the region of interest to form an associative data structure (DS). A graphical user interface (GUI) is generated that allows based on the associative data structure (DS) to retrieve the associated angiography upon a user selecting any one of the regions of interest (ROIa-c) on the graphical user interface (GUI).

Abstract: An iris recognition apparatus for recognizing iris in an eyeball is provided. In particular, an iris recognition apparatus including a reflection unit that reflects and transmits an image of an eyeball is provided. The reflection unit reflects and transmits an image of an eyeball. A first image collection unit collects a reflected image. A control unit extracts an iris pattern based on the collected image.

Abstract: A system for three dimensional imaging of motile objects includes an image sensor and a sample holder disposed adjacent to the image sensor. A first illumination source is provided and has a first wavelength and positioned relative to the sample holder at a first location to illuminate the sample. A second illumination source is also provided having a second wavelength, different from the first wavelength, and positioned relative to the sample holder at a second location, different from the first location, to illuminate the sample. The first and second illumination sources are configured to simultaneously, or alternatively, sequentially illuminate the sample contained within the sample holder. Three dimensional positions of the motile objects in each frame are obtained based on digitally reconstructed projection images of the mobile objects obtained from the first and second illumination sources. This positional data is connected for each frame to obtain 3D trajectories of motile objects.

Abstract: A method and system for determining a location of an occupant in a space include detecting a shape of an occupant in an image of a space; determining a location of the occupant on a floor of the space in the image, based on the shape of the occupant; and transforming the location on the floor in the image to a location of the occupant on the floor in the space.

Abstract: A method includes obtaining real-time imaging data of at least a sub-portion of an object and a region of interest therein. The method further includes displaying the real-time imaging data as the real-time imaging is obtained. The method further includes tracking extraction of a sample from the region of interest by an extraction device based on the real-time imaging data. The method further includes identifying an extraction location for the extracted sample based on the tracking and the real-time imaging data and generating a signal indicative thereof.

Abstract: An automatic calculation method for thickness calculation of a deposition layer in a Fin-type field-effect transistor (FinFET) is disclosed through mapping edge lines onto an Excel spreadsheet. The similar method is also applied to the thickness calculation of superlattice or multiple quantum well for a light emitting diode (LED). The edge lines are obtained and transformed from an electronic image taken by Transmission Electron Microscopy (TEM), Focus Ion Beam (FIB), Atomic Force Microscopy (AFM), or X-Ray Diffraction (XRD) of the device.

Abstract: A method for detecting a generalized passerby includes: acquiring an input image; determining whether a preset common feature of a wheel exists in the input image; selecting an image window at left side or right side or upper side of a center of a region where the preset common feature of the wheel is located in a case that the preset common feature of the wheel exists in the input image; inputting the selected image window into a preset upper-body classifier; detecting whether an upper body of a passerby exists in the selected image window and outputting a first detection result.

Abstract: A resolution evaluation section calculates a resolution evaluation value for each location within a monitoring target region excluding the presence area of an obstacle. A gazing point angle evaluation section calculates a gazing point angle evaluation value for each location within the monitoring target region excluding the presence area of the obstacle. The suitability calculation section calculates the suitability for each location within the monitoring target region excluding the presence area of the obstacle, on the basis of at least the resolution evaluation values and the gazing point angle evaluation values, the suitability indicating the degree to which the image of the monitoring target object placed at each location is suitable for the image recognition process. A display control section causes a display device to show regions within the monitoring target region which correspond to the suitabilities, in a mode commensurate with these suitabilities.

Abstract: An apparatus for video to text conversion using video analysis, which analyzes at least one object included in video data input from a video acquisition device and provides motion information and attribution information of the object in the form of a sentence or word arrangement according to patterns. The apparatus includes an analysis unit, a generation unit, a database unit and a production unit.

Abstract: Emission event data of an object of interest is acquired with a detector comprising a plurality of rings defining corresponding slices. Also, an amount of motion for each of a plurality of segments is determined with one or more processing units, wherein each segment corresponds to less than an axial field of view (AFOV) of the detector. Further, motion mitigation is performed for segments for which the amount of motion satisfies a threshold to provide motion mitigated data, and not performed for segments for which the amount of motion does not satisfy the threshold to provide non-mitigated data. An image is reconstructed using the motion mitigated data and the non-mitigated data, and the image is displayed on a display.

Abstract: A method of extracting ridge data includes selecting a point in the contour of an object from an image of the object, calculating a chamfer distance of the point in the contour, and determining whether the point in the contour is a ridge point based on relationships between the chamfer distance and chamfer distances of points in the contour adjacent to the point in the contour. A method of tracking a joint motion of an object includes acquiring initial information of the object including information on at least one ridge region representing a distribution of ridge points of the object, and tracking the joint motion of the object from temporally consecutive images of the object based on the initial information.

Abstract: Methods, apparatus, and other embodiments associated with objectively predicting disease aggressiveness using Spatially Aware Cell Cluster (SpACCl) graphs. One example apparatus includes a set of logics that acquires an image of a region of tissue, partitions the image into a stromal compartment and an epithelial compartment, identifies cluster nodes within the compartments, constructs a spatially aware stromal sub-graph and a spatially aware epithelial sub-graph based on the cluster nodes and a probabilistic decaying function of the distance between cluster nodes, extracts local features from the sub-graphs, and predicts the aggressiveness of a disease in the region of tissue based on the sub-graphs and the extracted features. Example methods and apparatus may employ a Support Vector Machine classifier to classify super-pixels within the image as stromal super-pixels or epithelial super-pixels.

Abstract: One example apparatus associated with detecting mitosis in breast cancer pathology images by combining handcrafted (HC) and convolutional neural network (CNN) features in a cascaded architecture includes a set of logics that acquires an image of a region of tissue, partitions the image into candidate patches, generates a first probability that the patch is mitotic using an HC feature set and a second probability that the patch is mitotic using a CNN-learned feature set, and classifies the patch based on the first probability and the second probability. If the first and second probabilities do not agree, the apparatus trains a cascaded classifier on the CNN-learned feature set and the HC feature set, generates a third probability that the patch is mitotic, and classifies the patch based on a weighted average of the first probability, the second probability, and the third probability.