Abstract: Provided are a method and an apparatus for detecting door image, and the method includes extracting an outline from the drawing; detecting an end point of the outline; detecting a directionality of the end point; detecting a peak adjacent the end point using the directionality; and detecting at least one window image using at least one of the number and position of the peak.

Abstract: An object counting device includes an image capturer and a processor. The image capturer captures an image sequence related to a gate within a field of view. When an object in the image sequence passes through an entry/exit reference corresponding to the gate, the processor determines a moving direction of the object. When the processor determines that the object moves from a first side of the gate towards a second side of the gate, the processor counts the object into a first accumulated number. When the object exits from the field of view, the processor records an exit position of the object. The processor determines whether to count the object into a second accumulated number according to the exit position.

Abstract: An imaging arrangement for capturing one or more views of a horizontal shelf of an autonomous retail store includes an image sensor positioned at a back portion of the horizontal shelf, a top mirror mounted at a top portion of the horizontal shelf, to enable the image sensor to capture a top view of one or more products on the horizontal shelf, a front mirror mounted at a front top portion of the horizontal shelf, and a back mirror mounted at a back top portion of the horizontal shelf, wherein the back mirror is inclined at a pre-defined angle with respect to the front mirror, and wherein the front and back mirrors enable the image sensor to capture a front view of the one or more products on the horizontal shelf.

Abstract: A computer-implemented technique is described for verifying the identity of a user using two components of face analysis. In a first part, the technique determines whether captured face information matches a previously stored structural face signature pertaining to the user. The structural face signature describes, at least in part, gross structural characteristics of the face that are largely invariant from pose to pose. In the second part, the technique determines whether the captured face information matches a dynamic face signature associated with the user. The dynamic face signature describes movement of parts of the face over a span of time as the user performs a gesture, and the correlation of different parts of the face during the movement. The technique reduces the risk that a malicious actor can successfully artificially duplicate the appearance of an authorized user.

Abstract: A method of image processing within an image acquisition device. In one embodiment an image including one or more face regions is acquired and one or more iris regions are identified within the one or more face regions. The one or more iris regions are analyzed to identify any iris region containing an iris pattern that poses a risk of biometrically identifying a subject within the image. Responsive to identifying any such iris region, a respective substitute iris region, containing an iris pattern distinct from the identified iris pattern to avoid identifying the subject within the image, is determined and the identified iris region is replaced with the substitute iris region in the original image.

Abstract: The present disclosure relates to a method, a device and a non-transitory computer storage medium for processing clothes information. The method includes: acquiring a number of wearing times for each piece of clothes in a clothes library within a preset time period, where the clothes library comprises a collection of information on clothes worn that is captured using a dressing mirror, and the number of wearing times is a counted number of times for each piece of clothes worn; determining clothes to be handled from the clothes according to the number of wearing times for each piece of clothes; and generating first prompt information for prompting to handle the clothes to be handled.

Abstract: A method for image processing and a mobile terminal, and a computer readable medium are disclosed. In one method, n number of first images and m number of second images are acquired. The first images and the second images are captured by a primary camera and a secondary camera respectively, and both the n and the m are integers greater than 2. A synthesizing-denoising process is performed on the n number of first images and the m number of second images respectively to obtain a primary image and a secondary image respectively. Depth information of the primary image is obtained based on the primary image and the secondary image. A blurring process for the primary image is then performed based on the depth information of the primary image to obtain a target image.

Abstract: An image analysis apparatus includes a processor including hardware. The processor extracts parts from each of a first image and a second image acquired after the first image, each of the extracted parts including an annular peripheral portion and a central portion having a color different from a color of the peripheral portion. The processor also sets the central portion as the analysis object region and calculates a brightness decrease degree of the analysis object region in the second image relative to the analysis object region in the first image.

Abstract: Embodiments of the present disclosure disclose a method and apparatus for processing an image. A preferred embodiment of the method comprises: receiving video data acquired by a web camera and decoding the video data to obtain at least one to-be-processed image containing a face image; determining a face region image in the to-be-processed image; and extracting facial feature information from the face region image, the facial feature information comprising at least one of the following: facial form information, eyebrow information or eye shape information. The embodiment acquires video data by means of a web camera, which ensures the quality of the acquired image, realizes the pre-processing of the to-be-processed image and is useful to improve the accuracy of the subsequent face recognition.

Abstract: Embodiments of the present disclosure disclose a method and apparatus for outputting information. The method includes: acquiring a first image and a second image, the first image including a first face image region, and the second image including a second face image region; generating an image matrix of the first image and an image matrix of the second image; inputting respectively the image matrix of the first image and the image matrix of the second image into a pre-trained convolutional neural network to obtain a characteristic vector of the first image and a characteristic vector of the second image; calculating a distance between the characteristic vector of the first image and the characteristic vector of the second image; and outputting, based on the calculated distance, information of an object relationship between an object the first face image region belongs and an object the second face image region belongs.

Abstract: The present disclosure provides a method and an apparatus of determining an image background, a device and a medium. The method includes: recognizing a face region in an image, and obtaining a face distance based on the face region; obtaining a face distance parameter of each pixel in the image based on the face distance; processing the face distance parameter and corresponding color parameter of each pixel in the image by applying a pre-trained image region segmentation model to determine an image region type corresponding to each pixel; determining a background region of the image based on the image region type corresponding to each pixel and performing preset background image processing on the background region.

Abstract: A system and a method to analyze a phenotypical response of cells to a treatment are disclosed in which a model development module receives images of a plurality of reference cell carriers and treatment information associated with the plurality of reference cell carriers, identifies parameters of cells in the image that distinguish those reference cell carriers to which the treatment has been applied from other reference cell carriers, and trains a model using the identified parameters. A high-content imaging system includes an image capture device, and the image acquisition module receives from the image capture device a plurality of images of cell carriers to be evaluated. The model application module applies the trained model to the plurality of images of the cell carriers to be evaluated to predict a concentration of the treatment applied to each of the cell carriers evaluated.

Abstract: Methods and systems for comparing content are provided. A recognizable object which appears in frames of a reference video file is recognized. A meta-feature of the recognizable object is determined. A first vector indicative of the meta-feature of the identified recognizable object in the reference video file is created. The meta-feature of the identified recognizable object which appears in a suspect video file is determined. A second vector indicative of the meta-feature of the identified recognizable object in the suspect video file is created. A correlation between the first vector and the second vector is determined. The correlation between the first vector and the second vector is indicative of a degree of confidence that the suspect video file is a copy of the reference video file.

Abstract: In one aspect, an example method includes (i) determining, by a computing system at a first time, a first height of a bumper of a leading vehicle relative to a reference height; (ii) determining, by the computing system at a second time that is later than the first time, a second height of the bumper relative to the reference height; (iii) making, by the computing system, a determination that the determined first height and the determined second height lack a threshold extent of similarity based on an established tolerance level; and (iv) responsive at least to making the determination that the determined first height and the determined second height lack the threshold extent of similarity based on the established tolerance level, causing, by the computing system, the light source to operate.

Abstract: A method of generating a three-dimensional physical map using different data sources includes receiving, at a computing device, topographic data, e.g., digital surface model data and/or digital elevation model data, for a geographic area and also receiving map area data, e.g., coordinates, scaling, and/or resolution data, for a subset area of the geographic area. The computing device generates map data, such as computer-readable three-dimensional (3D) printer data, based on the topographic data and the map area data, which can be used by a 3D printer or other additive manufacturing process to generate a three-dimensional physical map that depicts the topographic features of the subset area.

Abstract: A system and method for semantic segmentation using hybrid dilated convolution (HDC) are disclosed. A particular embodiment includes: receiving an input image; producing a feature map from the input image; performing a convolution operation on the feature map and producing multiple convolution layers; grouping the multiple convolution layers into a plurality of groups; applying different dilation rates for different convolution layers in a single group of the plurality of groups; and applying a same dilation rate setting across all groups of the plurality of groups.

Abstract: In a magnetic resonance apparatus and a method for generating MR image data of a subject with parallel imaging, a reference data set of the object is recorded, in which at least one partial section of the associated raw data space is completely filled with raw data according to the Nyquist condition, and an imaging data set is recorded for the generation of the MR image data on the basis of spin-echo-based signals, in which the associated raw data space is not completely recorded according to the Nyquist condition. A weighting matrix is calculated based on the reference data set, which is used to determine raw data points of the imaging data set not recorded during parallel imaging. The unrecorded raw data points of the imaging data set are calculated using the calculated weighting matrix.

Abstract: A system and related method are provided for sensor-based person recognition. The system has a data store including global data of a user, the global data including a globally unique identifier and sensed training data. The system further has a classifier to identify the user at a first time using the global data, augment the global data with first context information of the user captured at the first time, and identify the user at a second time by finding correlations between second context information and the first context information when using the global data fails, the second context information of the user captured at the second time.

Abstract: System, methods, and other embodiments described herein relate to improving detection of objects in a surrounding environment. In one embodiment, a method includes, in response to emitting a signal pulse, acquiring point cloud data about the surrounding environment as identified from the signal pulse reflecting from the surrounding environment. The method further includes determining which data points within the point cloud data are edge points by distinguishing the edge points from field points in the point cloud data according to edge characteristics. The method includes identifying an object in the surrounding environment according to a segment of the point cloud data that is bound by the edge points.

Abstract: Image data from two different devices is used to identify a physical interaction between two users to authenticate a digital interaction between the users.