Abstract: A technician performs a locate operation of an underground utility in a dig area of proposed excavation by applying one or more physical colored markers (e.g., paint, flags, other colored markers) to ground, pavement or other surface to indicate a presence or an absence of the underground utility in the dig area. A digital image of a geographic area comprising the dig area is displayed on a display device, and one or more electronic colored markers corresponding to the physical colored marker(s) are added to the displayed digital image so as to generate a marked-up image. Information relating to the marked-up image is electronically transmitted and/or electronically stored so as to document the locate operation.

Abstract: Featured are methods and systems to multiparametric non-linear dimension reduction (NLDR) methods for segmentation and classification of radiological images. Such methods for segmentation and classification of radiological images, includes pre-processing of acquired image data; and reconstructing the acquired image data using a non-linear dimension reduction technique so as to yield an embedded image representing all of the acquired, where the acquired image data comprises a plurality of different sets of image data of the same region of interest. Such NLDR methods and systems are particularly suitable for the ability to combine multiple input images into a single unit for increased specificity of diagnosis.

Abstract: A target line detection device includes a processor configured to execute a process. The process includes: detecting transition points in a brightness image obtained from a brightness component of an input image between pixels with a luminosity gradient in a first direction and pixels with a luminosity gradient in a second direction opposite to the first direction; and, based on a shape or a length or a combination thereof, of lines connecting together transition points that are within a specific distance of each other, extracting a line representing a detection target from the lines connecting together the transition points.

Abstract: An object area tracking apparatus has: a face detection unit for detecting a face area on the basis of a feature amount of a face from a supplied image; a person's body detection unit for detecting an area of a person's body on the basis of a feature amount of the person's body; and a main object determination unit for obtaining a priority for each of the objects by using detection results by the face detection unit and the person's body detection unit and determining a main object of a high priority, wherein for the object detected only by the person's body detection unit, the priority is changed in accordance with a past detection result of the object in the face detection unit.

Abstract: Disclosed are methods, systems, apparatuses, circuits and associated computer executable code for providing video based subject characterization, categorization, identification and/or presence response. According to some embodiments, there is provided a system including a video acquisition module, a video analytics module to extract subject features and a subject presence response module adapted to generate a response to an identification of a specific subject or group of subjects.

Abstract: A method for categorizing body shape is provided comprising the steps of providing a data set of body shape-defining measurements of a portion of the body of interest from a plurality of subjects' bodies, wherein the measurements define a silhouette and profile (front and side) perspectives of the portion of the body of interest; conducting a principal component (PC) analysis of the data set of measurements to calculate and generate PC scores; conducting cluster analysis using the PC scores as independent variables to produce cluster analysis results; and establishing one or more body shape categories from the cluster analysis results, thereby categorizing body shapes of the plurality of subjects. A shape prototyping system is also provided for designing a custom fit garment for an individual subject, the system being based on the method for categorizing body shape.

Abstract: Method and system for detecting objects of interest in a camera monitored area are disclosed. Statistical analysis of block feature data, particularly Sobel edge and spatial high frequency responses is used to model the background of the scene and to segregate foreground objects from the background. This technique provides a robust motion detection scheme prone to catching genuine motions and immune against false alarms.

Abstract: Provided is a method and system for tracking an object that may track a point into which an object is to move by combining the object in an image and position coordinates of the object acquired through a position tracking apparatus provided to the object and thereby displaying the position coordinates.

Abstract: In a method for monitoring water level of a water body, a monitoring system is configured to: capture a current image that has a portion of the water body, and a remaining portion aside from the portion of the water body; process the current image into a processed image that includes a water body region corresponding to the portion of the water body, and a background region corresponding to the remaining portion of the current image; mark, on the processed image, a plurality of virtual alert points according to a predetermined water level of the water body; determine whether at least one of the virtual alert points is located within the water body region of the processed image; and generate a monitoring result according to the determination thus made.

Abstract: A biometrics system captures and processes a handprint image using a structured light illumination to create a 2D representation equivalent of a rolled inked handprint. A processing unit calculates 3D coordinates of the hand from the plurality of images and maps the 3D coordinates to a 2D flat surface to create a 2D representation equivalent of a rolled inked handprint.

Abstract: An image processing device is provided, the image processing device comprising: an image input unit configured to be input with a frame image of an imaging area imaged by a camera; an image processing unit configured to process the frame image input to the image input unit, and detect an object imaged in the frame image; and an operation frequency determination unit configured to determine a frequency of an operation clock of the image processing unit according to the number of objects detected by the image processing unit, wherein the operation frequency determination unit lowers the frequency of the operation clock of the image processing unit as the number of objects detected by the image processing unit becomes smaller.

Abstract: A wearable article, such as glasses for a virtual reality program or glasses for an augmented reality application, using light sources and a photodetector that detects their light and outputs data indicative of the detected light. The wearable article uses one or more controllers to determine its position and/or orientation in the environment based on the data output by the photodetector. Data from one or more auxiliary motion sensing devices, e.g., a relative motion sensor such as an inertial device or other auxiliary motion device relying on acoustics, optics or electromagnetic waves within or outside the visible spectrum, can be used to supplement the position and/or orientation data from the photodetector.

Abstract: Provided are a method of reconstructing a biological tissue image, and a method and apparatus for acquiring a biological tissue image, which allow a biological tissue to be identified with higher accuracy than ever before. The reconstruction of the biological tissue image is performed by measuring spectra having a two-dimensional distribution correlated with a biological tissue section, and acquiring a biological tissue image from the two-dimensional measured spectra through utilization of the measured spectra and an classifier.

Abstract: An approach is provided for recognizing objects in media content. The capture manager determines to detect, at a device, one or more objects in a content stream. Next, the capture manager determines to capture one or more representations of the one or more objects in the content stream. Then, the capture manager associates the one or more representations with one or more instances of the content stream.

Abstract: A system and method is provided that identifies dynamic objects within a set of photographic images. The objects may be identified as dynamic based on depth data associated with the images. The depth data may also be used to determine the potential states of the dynamic objects within the set of images. A three-dimensional model be created in which the dynamic objects are displayed in accordance with one of the potential states.

Abstract: In one embodiment, at least one of number of times a frame is paused by a plurality of users (users) and attention-activity of the users for the frame is tracked for each frame of an asset (video etc.). An interactive version of at least one frame is pre-generated based on the tracking. The interactive version is stored to enable playing of the interactive version of the at least one frame. In another embodiment, pausing of a currently playing frame (frame) of the asset is determined. A determination to replace the frame is made based on at least one of attention-activity of a user in the frame, and detecting metadata, of the frame, specifying that the frame is to be replaced. An interactive version of the frame is generated, based on at least one of the attention of the user and the metadata, to replace the frame with the interactive version.

Abstract: A device may include a finger biometric sensor and a processor coupled thereto. The processor may acquire first and second finger matching biometric data based upon first and second finger placements adjacent the sensor. The processor may also perform a matching between the first and second finger matching data to generate composite finger matching data having an associated composite match score, perform another matching between the composite matching data and finger enrollment data when the composite match score exceeds a match threshold to generate an enrollment match score, and update the finger enrollment data with the composite matching data when the enrollment match score exceeds an enrollment threshold. In other embodiments, where the second finger matching data is acquired based upon a removal and replacement of the finger from adjacent the finger sensor, instead of or in addition to updating the finger enrollment data, a device function may be performed.

Abstract: The invention relates to a synthetic hologram (64A) comprising first elementary cells wherein first openings are respectively defined, said hologram being integrated into a first portion of a binary motif (60), said binary motif comprising at least one second portion wherein second elementary cells comprising second openings (66) are defined, said second openings having an average size equal to the average size of the first openings, with a 5% margin, and a random phase shift.

Abstract: An anti-counterfeit method for random textures and a recognizer thereof The method includes: A. selecting texture material 2 with texture elements 1 distributed randomly; B. a recognition system storing inherent recognition features J of texture elements 1; C. extracting random features S of distribution of texture element 1 and storing in the recognition system, texture material 2 being anti-counterfeit identification 3; D. the recognition system extracting features J? and random features S? of texture elements 1? to be recognized on anti-counterfeit identification 3?, and comparing respectively features J? with recognition features J as well as random features S? and random features S. If the compared results do not match, anti-counterfeit identification 3? is judged not to be anti-counterfeit identification 3. Otherwise, anti-counterfeit identification 3? is judged to be anti-counterfeit identification 3.

Abstract: The object detection apparatus prevents or eliminates detection errors caused by changes of an object which frequently appears in a background. To this end, an object detection apparatus includes a detection unit which detects an object region by comparing an input video from a video input device and a background model, a selection unit which selects a region of a background object originally included in a video, a generation unit which generates background object feature information based on features included in the background object region, and a determination unit which determines whether or not the object region detected from the input video is a background object using the background object feature information.