Abstract: First scanned images of the first container are received from a scanning device that show the contents of the interior of the first container before the first container is cut and opened. Second scanned images that are of the contents of the first container after the first container is cut and opened are also received. The images are analyzed and, based upon the analysis, selective modifications to the operating parameters of the container opening machine are determined and made.

Abstract: A method for dynamically measuring deformation of a rotating-body mold, including: (S1) subjecting an overall outer surface of the rotating-body mold to three-dimensional measurement to acquire an initial point cloud data; (S2) shooting, by a multi-camera system, the mold from different angles to obtain three-dimensional coordinates of marking points and coding points on the overall outer surface of the rotating-body mold; (S3) rotating the mold, and repeatedly photographing the marking points and the coding points on the mold surface under different angle poses; and calculating three-dimensional coordinates of the marking points and the coding points; and (S4) predicting a point cloud data of the outer surface under different angle poses based on a conversion relationship among the marking points to analyze a deformation degree of the mold during a rotation process.

Abstract: A 3D object sensing system includes an object positioning unit, an object sensing unit, and an evaluation unit. The object positioning unit has a rotatable platform and a platform position sensing unit. The object sensing unit includes two individual sensing systems which each have a sensing area. A positioning unit defines a positional relation of the individual sensing systems to one another. The two individual sensing systems sense object data of object points of the 3D object and provide the object data the evaluation unit. The evaluation unit includes respective evaluation modules for each of the at least two individual sensing systems, an overall evaluation module and a generation module.

Abstract: There is provided with an information processing apparatus. An acquisition unit acquires a plurality of pattern discrimination results each indicating a location of a pattern that is present in an image. A selection unit selects a predetermined number of pattern discrimination results from the plurality of pattern discrimination results. A determination unit determines whether or not the selected predetermined number of pattern discrimination results are to be merged, based on a similarity of the locations indicated by the predetermined number of pattern discrimination results. A merging unit merges the predetermined number of pattern discrimination results for which it was determined by the determination unit that merging is to be performed. A control unit controls the selection unit, the determination unit, and the merging unit to repeatedly perform respective processes.

Abstract: Occlusion of facial features may be detected and assessed in an image captured by a camera on a device. Landmark heat maps may be used to estimate the location of landmarks such as the eyes, mouth, and nose of a user's face in the captured image. An occlusion heat map may also be generated for the captured image. The occlusion heat map may include values representing the amount of occlusion in regions of the face. The estimated locations of the eyes, mouth, and nose may be used in combination with the occlusion heat map to assess occlusion scores for the landmarks. The occlusion scores for the landmarks may be used control one or more operations of the device.

Abstract: An image marking method includes acquiring an image and at least one feature to be marked in the image, searching for at least one target area matching the at least one feature to be marked in the image, and marking the at least one target area with a preset graphic. The feature corresponds to the preset graphic.

Abstract: A method, apparatus and system for calculating stress parameters is provided. The method comprises establishing a first image pyramid according to an image of a sample before deformation, and establishing a second image pyramid corresponding to the first image pyramid according to an image of the sample after deformation; starting from a top level in the first image pyramid, iteratively calculating displacement information on each level in the first image pyramid relative to a corresponding level in the second image pyramid based on a center point of each sub-region at each level in the first image pyramid and other positions in the sub-region; calculating strain information on the sample according to displacement information on a bottom level of the first image pyramid; and calculating stress parameters of the sample based on the strain information.

Abstract: A system including a computing device and camera is disclosed; the system configured for measuring three-dimensional attributes and associated performance measurements of a mechanical device. Some embodiments comprise a camera configured to capture images of the mechanical device and a computing device in communication with the camera. In some embodiments, the computing device is configured to access a first set of pixels associated with a first plurality of fiducials to calibrate a spatial resolution of the camera. A second image from the camera can be converted into a second set of pixels associated with each of the plurality of fiducials, which are attached to the mechanical device. The computing device can be further configured to compare the first and second set of pixels to determine the location of the plurality of fiducials on the mechanical device.

Abstract: A target object identification system includes a first camera, a second camera, and a processor. The first camera acquires an image of a first target region. The second camera synchronously acquires an image of a second target region. The second target region includes part or all of the first target region. Resolution of the first camera is higher than that of the second camera, and field of view of the second camera is greater than that of the first camera. The processor identifies first target objects according to the image of the first target region, and second target objects according to the image of the second target region, and determines association relationships between the first target objects in the image of the first target region and the second target object in the synchronously acquired image of the second target region.

Abstract: An illustrative image descriptor generation system generates a descriptor listing that includes a plurality of image descriptors corresponding to different feature points included within an image. Based on the descriptor listing, the system generates a geometric map representing the plurality of image descriptors in accordance with respective geometric positions of the corresponding feature points of the image descriptors within the image. Based on the geometric map, the system determines a proximity listing for a primary image descriptor within the plurality of image descriptors. The proximity listing indicates a subset of image descriptors that are geometrically proximate to the primary image descriptor within the image. Based on the proximity listing, the system selects a secondary image descriptor from the subset of image descriptors and combines the primary and secondary image descriptors to form a composite image descriptor. Corresponding methods and systems are also disclosed.

Abstract: A method for detecting change in a pair of sequential images. The method includes training a feature descriptor based on a generated training set of matching and non-matching image pairs. An imaging subsystem captures a pair of substantially sequential images of a field of view. The pair of captured images is aligned and then transformed into corresponding arrays of patches. A matching and non-matching probability is determined for each pair of adjacent patches based on the feature descriptor. Each pair of patches is classified as matching or non-matching based on a comparison of the matching and non-matching probability. A mask is generated identifying the pairs of patches that indicate change and then displayed overlaid on at least one of the sequential images to indicate change on a user interface.

Abstract: The present invention relates to an occupant monitoring method and apparatus therefor. A monitoring apparatus according to one aspect of the present invention may include a camera obtaining an image in a vehicle and a processor processing the image. Moreover, the processor may include a detecting module separating each region in which an object exists from the image, a classifying module classifying the object existing in the each separated region and a recognizing module recognizing a pose of an occupant if the object corresponds to the occupant.

Abstract: The present description relates to light patterns used in a live action scene of a visual production to encode information associated with objects in the scene, such as movement and position of the objects. A data capture system is enabled to differentiate between various groups of active markers attached to the objects in the scene. The groups of active markers emit particular wavelengths in strobing patterns predefined for the various groups. In some implementations, the groups are instructed to emit its assigned signature light pattern through a signal controller transmitting an initial key signature predefined for the group, followed by pattern signals to a control unit. The data representing the pattern is captured in illuminated and blank frames. Frames showing the light pattern are analyzed to extract information about the groups of active markers, such as distinguishing the groups and identifying the objects to which they are attached.

Abstract: This disclosure provides an apparatus and method for performing object detection based on images captured by a fisheye camera and an electronic device. The apparatus includes a memory and a processor coupled to the memory. The processor according to an embodiment is configured to: project an original image captured by the fisheye camera onto a cylindrical or spherical projection model, and perform reverse mapping to obtain at least two reversely mapped images, angles of view of the at least two reversely mapped images being towards different directions, detect objects in the reversely mapped images, respectively, and detect an object that is the same among the objects detected in the reversely mapped images. According to this disclosure, information in the wide field of view images obtained by capturing by the fisheye camera may be fully utilized.

Abstract: A method and system for segmenting a plurality of images. The method comprises the steps of segmenting the image through a novel clustering technique that is, generating a composite depth map including temporally stable segments of the image as well as segments in subsequent images that have changed. These changes may be determined by determining one or more differences between the temporally stable depth map and segments included in one or more subsequent frames. Thereafter, the portions of the one or more subsequent frames that include segments including changes from their corresponding segments in the temporally stable depth map are processed and are combined with the segments from the temporally stable depth map to compute their associated disparities in one or more subsequent frames. The images may include a pair of stereo images acquired through a stereo camera system at a substantially similar time.

Abstract: An action recognition method and apparatus related to artificial intelligence and include extracting a spatial feature of a to-be-processed picture, determining a virtual optical flow feature of the to-be-processed picture based on the spatial feature and X spatial features and X optical flow features in a preset feature library, where the X spatial features and the X optical flow features include a one-to-one correspondence, determining a first type of confidence of the to-be-processed picture in different action categories based on similarities between the virtual optical flow feature and Y optical flow features, where each of the Y optical flow features in the preset feature library corresponds to one action category, X and Y are both integers greater than 1, and determining an action category of the to-be-processed picture based on the first type of confidence.

Abstract: Detecting an object in an image of pixels is disclosed. The method includes: obtaining a position of a mask covering at least one pixel of an image; obtaining a predefined neighbourhood of pixels around the mask and dividing this neighbourhood into zones; for each zone, calculating a mean and variance of values of the pixels of the zone; calculating, for each possible pair of zones, a difference between the zones; determining whether a background of the mask is multimode or monomode according to the differences; calculating a variance of the values of the neighbourhood pixels using a formula for calculating the variance dependent on the monomode or multimode type of the background; calculating a signal to noise ratio for the mask position using the variance of the values of the pixels of the neighbourhood obtained; and detecting an object when the signal to noise ratio is above a threshold.

Abstract: An image object recognition method, apparatus, and computer device are provided. The image object recognition method includes: performing feature extraction in the direction of a horizontal angle of view and in the direction of a vertical angle of view of an image respectively, to extract a lateral feature sequence and a longitudinal feature sequence of the image; fusing the lateral feature sequence and the longitudinal feature sequence to obtain a fused feature; activating the fused feature by using a preset activation function to obtain an image feature; and recognizing an object in the image by decoding the image feature. This solution can improve the efficiency of the object recognition.

Abstract: An apparatus for scaling images is provided that includes at least two input ports, a scaling component coupled to the at least two input ports, the scaling component including a plurality of scalers, the scaling component configurable to map any scaler to any input port of the at least two input ports and configurable to map more than one scaler to any input port, and a memory coupled to the at least two input ports and to outputs of the plurality of scalers, the memory configured to store image data for each input port and scaled image data output by the plurality of scalers.

Abstract: An image segmentation system is discloses that provides one or more possible contours of a feature of an image, in parallel, that respectively correspond to different interpretations of the image. First, a relatively large set of possible contours are generated in accordance with an image segmentation algorithm. Subsequently, this set of possible contours is reduced to a few candidates reflecting representative solutions corresponding to one or more desired applications.