Abstract: A computer-implemented method for entity detection is described. In one embodiment, an entity passing through a perimeter of a predefined area is detected via a camera. Upon detecting the entity passing through the perimeter of the predefined area, a type of the entity is classified from an image of the entity captured by the camera. Upon classifying the type of the entity, a feature of the entity is detected from the image of the entity. An identifier is assigned to the entity based on the type and the detected feature of the entity. The identifier distinguishes the entity from another entity of a same type.

Abstract: In the context of a method for the analysis of image data representing a three-dimensional volume (10, 20) of biological tissue, for each of a number of subvolumes at least two error probability values (41, 42, 43, 44) are generated, each of the values (41, 42, 43, 44) indicating a probability of a type of imaging error, the totality of subvolumes constituting the three-dimensional volume (10, 20). A single consolidated error probability value (51) is determined for each of the number of subvolumes, based on the at least two error probability values (41, 42, 43, 44). Subsequently, the image data is analyzed to obtain a physiologically relevant conclusion applying to a plurality of subvolumes, weighting in the analysis the image data of a given subvolume of the plurality of subvolumes according to the consolidated error probability (51) of the subvolume.

Abstract: A system and methods for detecting polyps using optical images acquired during a colonoscopy. In some aspects, a method includes receiving the set of optical images from the input and generating polyp candidates by analyzing the received set of optical images. The method also includes generating a plurality of image patches around locations associated with each polyp candidate, applying a set of convolutional neural networks to the corresponding image patches, and computing probabilities indicative of a maximum response for each convolutional neural network. The method further includes identifying polyps using the computed probabilities for each polyp candidate, and generating a report indicating identified polyps.

Abstract: A computed tomography (CT) method and apparatus including a radiation source configured to produce radiation directed to an object space, and a plurality of detector elements configured to detect the radiation produced from the radiation source through the object space and generate projection data. A rotation mount is configured to rotate the radiation source around the object space. Processing circuitry is configured to cause the rotation mount to rotate the radiation source, and to receive the projection data. The projection data includes a plurality of projection data sets. The processing circuitry calculates a set of weights based on the projection data sets, calculates a set of pre-weights based on the weights, and minimizes a penalized weighted least-squares cost function to produce a reconstructed image. The cost function is a sum of a weighted least-squares term, weighted using the weights, and a penalty term weighted using the pre-weights.

Abstract: A system and methods for polyp detection using optical colonoscopy images are provided. In some aspects, the system includes an input configured to receive a series of optical images, and a processor configured to process the series of optical images with steps comprising of receiving an optical image from the input, constructing an edge map corresponding to the optical image, the edge map comprising a plurality of edge pixel, and generating a refined edge map by applying a classification scheme based on patterns of intensity variation to the plurality of edge pixels in the edge map. The processor may also process the series with steps of identifying polyp candidates using the refined edge map, computing probabilities that identified polyp candidates are polyps, and generating a report, using the computed probabilities, indicating detected polyps. The system also includes an output for displaying the report.

Abstract: There is provided an image processing apparatus including a distance information generation portion configured to generate first distance information about an object to be measured based on a phase difference between images provided by a plurality of first cameras having a first base length, and generate second distance information about the object to be measured based on a phase difference between images provided by a plurality of second cameras having a second base length that is different from the first base length; and a distance extraction portion configured to extract distance information from an imaging position and the object to be measured based on the first distance information and the second distance information.

Abstract: In an example embodiment, a computer-implemented method receives image data from one or more sensors of a moving platform and detecting one or more objects from the image data. The one or more objects potentially represent extremities of a user associated with the moving platform. The method processes the one or more objects using two or more context processors and context data retrieved from a context database. The processing produces at least two confidence values for each of the one or more objects. The method filters at least one of the one or more objects from consideration based on the confidence value of each of the one or more objects.

Abstract: Described embodiments detect changes in a scene over time using first and second images of the scene. A non-coherent intensity change detector detects large-scale changes between the first image and the second image and generates a large-scale change value for pairs of corresponding pixel locations in the first and second images. If the large-scale change value for a given pair of pixel locations reaches a threshold, a coherent change detector is used to detect small-scale changes between the first and second images. A small-scale change value is generated for the given pairs of pixel locations in the images. A composite change value is generated by combining the large-scale change value and the small-scale change value for each pixel pair. The change thresholds are used to determine whether a change in the scene has occurred over the time period.

Abstract: Methods and systems of detecting tampering in a digital image includes using hybrid large feature mining to identify one or more regions of an image in which tampering has occurred. Detecting tampering in a digital image with hybrid large feature mining may include spatial derivative large feature mining and transform-domain large feature mining. In some embodiments, known ensemble learning techniques are employed to address high feature dimensionality. detecting inpainting forgery includes mining features of a digital image under scrutiny based on a spatial derivative, mining one or more features of the digital image in a transform-domain; and detecting inpainting forgery in the digital image under scrutiny at least in part by the features mined based on the spatial derivative and at least in part by the features mined in the transform-domain.

Abstract: Inspection and classification system have a customs data repository for automatic customs inspection of parcels comprising a data acquisition module configured to acquire information about parcels by input devices, wherein the information indicates customs classification criterias, the acquisition module further configured to communicate the information to the customs data repository; wherein the data repository stores the following data: information about parcels; parameters; attributes and big-data; a processor coupled with memory configured to map the information according with the parameters and attributes, wherein the mapped information of the parcel is a cluster; the processor is further configured for predicting customs classification of the parcel based upon comparison between parameters/attributes of the cluster and parameters/attributes of clusters stored in the big-data, wherein clusters stored in the big-data are were previously inspected, and wherein the cluster assumes a customs classification o

Abstract: A method for estimating a fracability index for a geological location includes determining a fabric metric and a mineralogical composition metric for a geological sample extracted from a geological location and estimating a fracability index for the geological location from the fabric metric and the mineralogical composition metric. The fabric metric may be a grain related measurement such as grain size or angularity, or a pore-space related measurement such as pore area, diameter, aspect ratio, and circumference, or statistics associated with such measurements. In certain embodiments, determining the mineralogical composition metric includes detecting a prevalence of at least one organic proxy within the geological sample such as vanadium, iron, uranium, thorium, copper, sulfur, zinc, chromium, nickel, cobalt, lead and molybdenum. Determining the mineralogical composition metric may also include detecting a prevalence of one, two, or all of siliciclastics, carbonate and clay.

Abstract: There is provided an imaging unit comprising at least one image sensor, a measuring instrument including at least one marker, a position computing unit, a determining unit, and an output controller, wherein the imaging unit is configured to acquire an image comprising a user and the marker, and provide the acquired image to the position computing unit, wherein the position computing unit is configured to compute a position of the marker with respect to the user based on the image provided by the imaging unit, and further provide the computed position to the determining unit, wherein the determining unit is configured to determine whether the computed position of the marker matches a retrieved measurement position, and further output the result of the determination to the output controller, and wherein the output controller is configured to provide an indication when the marker position matches the measurement position.

Abstract: Mechanisms for generating a true depth profile of a body of water are disclosed. A depth profile tensor that identifies a depth at each of a plurality of locations of the body of water is accessed. The depth profile tensor identifies, for at least some locations of the plurality of locations, multiple depths. The depth profile tensor is converted to a binary potential depth image that depicts multiple potential depths for the at least some locations. The multiple potential depths are reduced, by a morphological filter process, to a single depth for the at least some locations to generate a binary depth image. The binary depth image is converted to the true depth profile.

Abstract: Disclosed are systems and methods for detecting moving objects. A computer-implemented method for detecting moving objects comprises obtaining a streaming video captured by a camera; extracting an input image sequence including a series of images from the streaming video; tracking point features and maintaining a set of point trajectories for at least one of the series of images; measuring a likelihood for each point trajectory to determine whether it belongs to a moving object using constraints from multi-view geometry; and determining a conditional random field (CRF) on an entire frame to obtain a moving object segmentation.

Abstract: A vehicular control system includes a forward viewing camera that views forward through the vehicle windshield and a control including an image processor that processes image data captured by the camera. Responsive at least in part to processing of captured image data, (i) at least one road characteristic of a road along which the vehicle is traveling is detected, (ii) other vehicles exterior the vehicle are detected, and (iii) road curvature of the road along which the vehicle is traveling is determined. Data derived at least in part from captured image data and at least in part relevant to a current geographic location of the vehicle is wirelessly communicated from the vehicle to a remote data receiver located remote from the vehicle. Based at least in part on image data processed by the image processor, speed of the vehicle is controlled.

Abstract: There is provided an information processing apparatus including an image acquisition unit configured to acquire a dish image obtained by shooting a single or multiple dishes, and a first dish recognition unit configured to recognize the single or multiple dishes included in the dish image with reference to dish data selected, from dish data registered in advance, based on a condition regarding at least one of a person relating to the dish image, a shooting environment of the dish image, a shooting place of the dish image, and a shooting time of the dish image.

Abstract: A method and system can analyze, reconstruct, and/or denoise an image. The method and system can include interpreting a signal as a potential of a Schrödinger operator, decomposing the signal into squared eigenfunctions, reducing a design parameter of the Schrödinger operator, analyzing discrete spectra of the Schrödinger operator and combining the analysis of the discrete spectra to construct the image.

Abstract: Systems and methods are provided for tracking a dribbling and/or passing motion associated with a person engaged in either a training session for a sporting event or the live play of the sporting event. In sporting events, a dribbling motion can be associated with a repetitive movement or a short trajectory sequence between changes of direction of a ball, puck or other object used in the sporting event. A passing motion can be associated with the movement of the ball, puck or other object between two people during the sporting event. The system can use one or more sensors to capture information about a person dribbling and/or passing an object and at least one processor to analyze the information to determine and evaluate one or more characteristics associated with the dribbling, the passing motion, or a transition from dribbling to passing.

Abstract: A computer-implemented method of positioning a video frame within a collage cell includes, for a given one of a plurality of video frames, generating a polygon encompassing a portion of the respective video frame containing at least one visual element. The polygon has a center position corresponding to a first point within the respective video frame. The center position of the polygon of a given frame is then changed to a new center position based at least in part on an average center position of polygons encompassing portions of at least two consecutive video frames containing the visual element(s). The new center position corresponds to a second point within the given video frame. Next, a cropped portion of the given video frame encompassed by the polygon having the new center position is generated and displayed within a collage cell of a graphical user interface.

Abstract: A vehicle hitch detection system is provided. The vehicle hitch detection system includes a camera arranged to capture images of a vehicle hitch and a controller processing the images to detect a powered hitch ornament connected to the hitch based on the processed images when an electrical hitch connection is detected. The controller may further control a driver assistance system based on the detected hitch ornament to enable or disable the system.