Abstract: The invention relates to a method for configuring a monitoring system which is based on a recording of altitude maps, comprising the following steps:—an altitude map of a monitored area is recorded with the monitoring system in a state in which no objects or persons to be detected are located in the monitored area,—determination of destruction points, caused by obstacles, in the altitude map which is recorded in this way,—definition of a detection area as a component area of the altitude map in such a way that all the disruption points, or at least some of said disruption points, lie outside the detection area,—setting of an evaluation unit of the monitoring system such that it only evaluates movements within the detection area. The invention also relates to a correspondingly configurable monitoring system.

Abstract: A computing device reads an entire image of an object. The entire image is spliced by a plurality of part images. A user selects an area on the entire image. The computing device determines a first number of first pixel points between a center point of the selected area and a center point of each covered image. The converted images are part images that the selected area covers. The coordinate values of the center point of the selected area are calculated according to the first number of pixel points and a size of each pixel point of the entire image. The computing device calculates coordinate values of each point of a selected area according to the size of each pixel point and the coordinate values of the center point of the selected area.

Abstract: Systems and methods use cameras to provide autonomous navigation features. In one implementation, a traffic light detection system is disclosed. The system may include at least one image capture device configured to acquire a plurality of images of an area forward of the vehicle, the area including a traffic lamp fixture having at least one traffic light. At least one processing device may be configured to align areas of the plurality of images corresponding to the traffic light, based on a determined center of brightness, expand each pixel within the aligned areas, determine a set of average pixel values including an average pixel value for each set of corresponding expanded pixels within the aligned areas, and determine, based on the set of average pixel values, whether the traffic light includes an arrow.

Abstract: According to an example, a face capture and matching system may include a memory storing machine readable instructions to receive captured images of an area monitored by an image capture device, and detect one or more faces in the captured images. The memory may further store machine readable instructions to track movement of the one or more detected faces in the area monitored by the image capture device, and based on the one or more tracked detected faces, select one or more images from the captured images to be used for identifying the one or more tracked detected faces. The memory may further store machine readable instructions to select one or more fusion techniques to identify the one or more tracked detected faces using the one or more selected images. The face capture and matching system may further include a processor to implement the machine readable instructions.

Abstract: An image processing device includes a processor; and a memory which stores a plurality of instructions which, when executed by the processor, cause the processor to execute: acquiring a picked image; selecting pixels, which are adjacent to each other, to be connected based on value of the pixels in the image; generating a pixel connected area which includes the connected pixels; extracting a feature point from an outer edge of the pixel connected area; and calculating a moved amount of the feature point on the basis of the feature point of a plurality of images that have been picked at the first time and the second time by the acquiring.

Abstract: Information from a position and/or gesture detection system can be embedded in a Web page, or other such presentation of content, and used to select or otherwise interact with content on the page. In some embodiments, video is captured and displayed showing a current view of the user. Position data corresponding to the video is provided and used to determine directions and extents of motion without having to do significant amounts of image processing. The position data is used to determine locations on the page where the user is attempting to provide input, such as to select an item of content. The content can be modified and/or rendered to appear to be associated with the user in the rendered view. Information from multiple gesture systems can be combined on a single page, and information from one or more gesture systems can be shared among multiple pages and devices.

Abstract: A method, apparatus, and manufacture for smiling face detection is provided. For each frame, a list of new smiling faces for the frame is generated by performing smiling face detection employing an object classifier that trained is to distinguish between smiling faces and all objects in the frame that are not smiling faces. For the first frame, the list of new smiling faces is employed as an input smiling face list for the next frame. For each frame after the first frame, a list of tracked smiles for the frame is generated by tracking smiling faces in the frame from the input smiling list for the frame. Further, a list of new smiling faces is generated for the next frame by combining the list of new smiling faces for the frame with the list of tracked smiles for the frame.

Abstract: The present invention provides a method and device for implementing original handwriting trace, and an electronic device. The method comprises: continuously sampling handwriting trace in time order, and detecting location information and the actual stroke widths at the sampling points; for every two adjacent sampling points, determining the former point as the starting sampling point, determining the latter point as the ending sampling point, using a line connecting the two points as the center line of the stroke between the two sampling points, obtaining location information of and the corresponding longitudinal stroke width at each point on the center line, and determining, according to the location information of and the corresponding longitudinal stroke width at each point on the center line, the fill gray value of each pixel in the stroke; and filling, according to the fill gray values, the corresponding pixels, and displaying the pixels.

Abstract: An approaching-object detector for detecting an object approaching an own vehicle includes: a memory; and a processor configured to perform a process, the process including extracting a plurality of corresponding feature points from chronologically captured images, which are obtained by capturing the object using an imaging device provided for the own device, detecting a behavior among the captured images in regard to each of the plurality of feature points, determining whether or not the behavior is random in regard to each of the plurality of feature points, and determining whether or not the object is approaching the own vehicle based on a behavior of a feature point whose behavior is determined to be not random among the plurality of feature points, and outputting a result of the determination.

Abstract: There is disclosed a technique for use in processing vectorized elements on a mobile computing device. A vector list is received, wherein the list comprises a set of vectors having positional and magnitude values associated with identified markers. A first test angle and stride size is determined. Vectors falling within a boundary defined by the first test angle and first stride size are analyzed and a likelihood the vectors form a line is determined. An increment size is adjusted if a positive determination result occurs. Vectors that intersect with a line are identified, wherein the vectors include vectors determined to fall with the boundary defined by the first test angle and first stride size. Based on a first policy, vectors that intersect the line are identified. A report including anchor information associated with the identified vectors is created.

Abstract: Provided are examples of a detecting engine for identifying detections in compressed scene pixels. For a given compressed scene pixel having a set of M basis vector coefficients, set of N basis vectors, and code linking the M basis vector coefficients to the N basis vectors, the detecting engine reduces a spectral reference (S) to an N-dimensional spectral reference (SN) based on the set of N basis vectors. The detecting engine computes an N-dimensional spectral reference detection filter (SN*) from SN and the inverse of an N-dimensional scene covariance (CN). The detecting engine forms an M-dimensional spectral reference detection filter (SM*) from SN* based on the compression code and computes a detection filter score based on SM*. The detecting engine compares the score to a threshold and determines, based on the comparison, whether the material of interest is present in the given compressed scene pixel and is a detection.

Abstract: A system and method of processing an image is disclosed. A particular method of determining whether a particular pixel of an image is a feature includes receiving data corresponding to a plurality of pixels (from the image) surrounding the particular pixel. The method further includes determining a set of comparison results, each corresponding to one of the plurality of pixels and indicating a result of comparing an attribute value corresponding to one of the plurality of pixels to a comparison value (based on a particular attribute value of the particular pixel and a threshold value). The method further includes performing a processor-executable instruction that, when executed by a processor, causes the processor to identify a subset of the set of comparison results that indicate the particular pixel is the feature. The identified subset may be a consecutive order of pixels of the plurality of pixels.

Abstract: A method, system, and device for analyzing images captured by a vehicle-based camera includes establishing a communication connection between a mobile communication device and an in-vehicle computing system. Scanning data may be retrieved from a scanning data server by the mobile communication device and, in some embodiments, forwarded to the in-vehicle computing system. A vehicle-base camera may be used to capture one or more images. An image analysis module of the in-vehicle computing system or mobile communication device may be used to analyze the captured image(s) for a match between the image(s) and the scanning data. In response to identifying a match, the mobile communication device may notify the scanning data server of the identified match.

Abstract: A method of identifying anomalies in images produced using an imaging device (70). The method comprises receiving (10), (12) first and second pluralities of candidate anomalies, the candidate anomalies being identified in subsequent images produced with an imaging device. A constellation match (14), (16), (18), (19) is carried out between the first and second pluralities of candidate anomalies to identify a correlation therebetween, represented by a constellation match value. A plurality of constellation match values is determined with a different relative x-y shift between the first and second pluralities of candidate images. If a good correlation is found at a particular x-y shift then the candidate anomalies are common between the first and second images, which is indicative of the first and second images including anomalies.

Abstract: A three-dimensional object detection device includes an image capturing unit, an image conversion unit, a three-dimensional object detection unit, a three-dimensional object assessment unit and a control unit. The image conversion unit converts images obtained by the image capturing unit to create bird's-eye view images. The three-dimensional object detection unit detects a presence of a three-dimensional object within a detection area based on differential waveform information or edge information. The stationary three-dimensional object assessment unit assesses whether the detected three-dimensional object is a shadow of a tree along a road traveled by the host vehicle. The three-dimensional object assessment unit assesses whether the three-dimensional object detected is a vehicle within the detection area.

Abstract: Shape data of a patient's crown and volumetric imagery of the patient's tooth are received. A determination is made of elements that represent one or more crowns in the shape data. A computational device is used to register the elements with corresponding voxels of the volumetric imagery. A tooth shape is determined from volumetric coordinates and radiodensities.

Abstract: A biometric image sensor system and method is disclosed which may comprise a first light source having a first wavelength ?1, a second light source having a second wavelength ?2, a photodetector configured and positioned to receive light of the first wavelength ?1 and light of the second wavelength ?2 reflecting from a biometric object being imaged and to produce a first output indicative of the amount of reflectance of the light of the first wavelength ?1 and a second output indicative of the amount of reflectance of the light of the second wavelength ?2, and a computing device configured to compare the difference between the first output and the second output with an authenticity threshold.

Abstract: A method (100) that generates attenuation correction maps for the reconstruction of PET data using MR images, such as, MR ultra-fast TE (UTE) images, Dixon MR images, as well as MR images obtained using other MR imaging methods.

Abstract: A human tracking method using a color histogram is disclosed. The human tracking method using the color histogram according to the present invention can more adaptively perform human tracking using different target color histograms according to the human poses, instead of applying only one target color histogram to the tracking process of one person, such that the accuracy of human tracking can be increased. The human tracking method includes performing color space conversion of input video data; calculating a state equation of a particle based on the color-space conversion data; calculating the state equation, and calculating human pose-adaptive observation likelihood; resampling the particle using the observation likelihood, and estimating a state value of the human; and updating a target color histogram.

Abstract: An image tracking device and an image tracking method thereof are provided. The image tracking device includes an image capture interface, a storage means, and a processor means. The storage means has a multi-dimensional storage space for storing a plurality of first images, each dimension of the multi-dimensional storage space being corresponding to a feature-related variance of a multi-dimensional variance. The processor means is configured to execute the following operations: marking a second image in the picture frame; calculating a multi-dimensional variance between the second image and each of the first images separately; determining whether the second image contains the object according to the multi-dimensional variance calculated; and if the second image is determined as one containing the object, storing the second image as one of the first images, in a specific subspace of the multi-dimensional storage space according to the multi-dimensional variance calculated.