Abstract: A security system (10) includes an image information acquisition unit (11) that acquires input image information on an image taken of a person in a store, a tracking unit (12) that tracks an action of a hand of the person based on the input image information, and a suspicious action detection unit (13) that detects a suspicious action of the person based on the tracked action of the hand. A security system, a security method, and a security program capable of accurately detecting a suspicious action are thereby provided.

Abstract: A method may include receiving, via at least one processor, a plurality of images representative of a property and determining whether two or more images of the plurality of images correspond to reference image data associated with the property. The method may then involve combining the images to generate a digitally stitched image that corresponds to the reference image data in response to the images corresponding to the reference image data and comparing the digitally stitched image to the reference image data to identify features associated with the property. The method may also involve updating a model representative of the property based on the features and generating an updated insurance policy associated with the property based on the model. Afterwards, the method may send a notification indicative of the updated insurance policy to a computing device.

Abstract: A method, device and equipment for reconstructing a PET image are provided. The method includes acquiring a prior image comprising an anatomical image and an autocorrelation feature image, the autocorrelation feature image being determined based on gray-level co-occurrence matrix of the anatomical image; and acquiring a feature value of the prior image; reconstructing the PET image according to the feature value and an iterative algorithm.

Abstract: A surgical image capture and display system includes a handheld image capture and pointing device and a display assembly. An image is captured by an image sensor of the handheld device and displayed on the display assembly. The image sensor detects light emitted by one or more beacons of the display assembly. The system determines, based on the light emitted by the one or more beacons, a position or orientation of the handheld device relative to the display assembly. The system updates display of a graphical user interface comprising the image on the display assembly in accordance with the determined position or orientation of the handheld device.

Abstract: A system for computer-aided triage includes and/or interfaces with a computing system. A method for computer-aided triage includes receiving a data packet including a set of images; and processing the set of images to determine a suspected condition and/or associated features. Additionally or alternatively, the method can include any or all of: preprocessing the set of images; triggering an action based on the suspected condition and/or associated features; determining a recipient based on the suspected condition; preparing a data packet for transfer; transmitting information to a device associated with the recipient; receiving an input from the recipient and triggering an action based on the input; aggregating data; and/or any other suitable processes.

Abstract: A visual recognition based method for projecting patterned light includes: projecting a calibration image onto a projection screen by a projection module; capturing the calibration image by an image-capturing module to obtain a calibration information between the projection module and the image-capturing module; capturing an object by the image-capturing module to obtain a to-be-recognized image of the object; detecting the object in the to-be-recognized image and acquiring a plurality of feature points associated with a plurality of feature areas of the object in the to-be-recognized image; retrieving a plurality of target feature points corresponding to a target object from the feature points; obtaining a projection coordinate of the target feature points\ according to the calibration information and providing the projection coordinate to the projection module; and projecting a projection pattern with shape corresponding to the target object onto the object by the projection module according to the projecti

Abstract: A system for validating the road object data is provided. The system, for example, receives the road object data for a geographic region and determines, from a map database, a state of ground truth data associated with the geographic region. The state of the ground truth data comprises at least one of partial ground truth data and complete ground truth data. Further, the road object data is validated based on the determined state of the ground truth data. The validation of the road object data includes performing a first validation operation when the state of the ground truth data is the partial ground truth data and performing a second validation operation when the state of the ground truth data is the complete ground truth data.

Abstract: The present invention relates to a system and a method for calibration between coordinate systems of a 3D camera and a medical imaging apparatus. The calibration system includes a calibration tool having markers and a reference point that is aligned with a center of the medical imaging apparatus to serve as an origin of the coordinate system. Positions of the markers in the coordinate system of the medical imaging apparatus are calculated according to relative positions of the markers with respect to the reference point. A 3D camera captures images to determine positions of the markers in the coordinate system of the 3D camera. A calculation device calibrates the coordinate system of the 3D camera and the coordinate system of the medical imaging apparatus using the positions of the markers in the coordinate system of the 3D camera and the p in the coordinate system of the medical imaging apparatus.

Abstract: A driver monitor detects, based on face images obtained by capturing the face of a driver of a vehicle at different times, a color of the face of the driver and a face orientation angle of the driver in each face image; stores, when a face orientation angle detected from a first face image captured at a first time is included in a predetermined range of face orientation angles, the color detected from the first face image in a memory; and determines that the color of the face is abnormal, when a face orientation angle detected from a second face image captured at a second time later than the first time is included in the range of face orientation angles and a difference between the color detected from the second face image and the color stored in the memory exceeds a variance threshold.

Abstract: An object detection and classification verification system for a vehicle includes a projection system configured to project a three-dimensional (3D) scene pre-captured at a known distance and comprising at least one known object onto a surface in front of the vehicle a controller configured to verify a performance of an object detection and classification routine by performing the object detection and classification routine on the projected 3D scene to generate a set of results, comparing the set of results to a set of expected results associated with the projected 3D scene, and based on the comparing, determining whether the performance of the object detection and classification routine satisfies a predetermined threshold metric.

Abstract: One example method includes identifying dissimilar items in a data set. A data set may be walked one or more times and the nodes or vertices of the data set may be scored based on the number of times the nodes are touched during the walks. Scores below a threshold score are determined to be dissimilar nodes in the data set. This allows a diverse set of nodes to be identified. A dissimilar data set may be used to prevent unintentional bias in algorithmic training.

Abstract: Systems and methods for automatic detection of surgical specialty type and procedure type are disclosed. One or more classification networks may be applied to automatically process input surgical image data in order to recognize and determine a surgical specialty type and a surgical procedure type depicted in the input image data. Based on the determination made by the system, one or more output indications may be generated and one or more surgical devices may be automatically controlled, such as by being optimized for use during the surgical procedure type and/or surgical specialty type represented by the input image.

Abstract: There is provided a learning method and a learning device for performing transfer learning on an object detector that has been trained to detect first object classes such that the object detector is able to detect second object classes. Further, a testing method and a testing device are provided to allow at least part of the first object classes and the second object classes to be detected by using the object detector having been trained through the transfer learning. Accordingly, a detection performance can be improved for the second object classes that cannot be detected through training data set corresponding to the first object classes.

Abstract: This application provides a method of generating a description for a picture set performed at a computer device, and a storage medium. The method includes: acquiring a picture set to be processed; performing picture feature extraction on each picture in the picture set to acquire a picture feature corresponding to the picture, and forming a picture feature sequence corresponding to the picture set by using the picture features corresponding to the pictures; performing scene feature extraction on a picture feature sub-sequence corresponding to each scene in the picture feature sequence to acquire a scene feature corresponding to the scene, and forming a scene feature sequence corresponding to the picture set by using the scene features corresponding to the scenes; and generating textual description information of the picture set according to the picture feature sequence and the scene feature sequence that correspond to the picture set.

Abstract: Methods, systems, and computer-readable storage media for determining that a subject is a live person include capturing one or more images of two eyes of a subject. The one or more images, from each of the two eyes are used to obtain respective corneal reflections. Depth information associated with a scene in front of the subject is determined, based on an offset between the respective corneal reflections. A determination is made, based at least on the depth information, that the subject is a live person. Responsive to determining that the subject is a live person, an authentication process is initiated to authenticate the subject.

Abstract: Systems and methods are disclosed to objectively identify sub-second behavioral modules in the three-dimensional (3D) video data that represents the motion of a subject. Defining behavioral modules based upon structure in the 3D video data itself— rather than using a priori definitions for what should constitute a measurable unit of action— identifies a previously-unexplored sub-second regularity that defines a timescale upon which behavior is organized, yields important information about the components and structure of behavior, offers insight into the nature of behavioral change in the subject, and enables objective discovery of subtle alterations in patterned action. The systems and methods of the invention can be applied to drug or gene therapy classification, drug or gene therapy screening, disease study including early detection of the onset of a disease, toxicology research, side-effect study, learning and memory process study, anxiety study, and analysis in consumer behavior.

Abstract: A device includes: a distribution information acquiring part configured to acquire, based on an image in which a plurality of cells that are cultivated in a predetermined area are imaged, distribution information relating to a distribution in the predetermined area of the plurality of cells; and a determination part configured to determine a cultivated state of the plurality of cells based on the distribution information acquired by the distribution information acquiring part.

Abstract: A system and method for providing image guidance for placement of one or more medical devices at a target location. The system can determine one or more intersections between a medical device and an image region based at least in part on first emplacement data and second emplacement data. Using the determined intersections, the system can cause one or more displays to display perspective views of image guidance cues, including an intersection indicator in a virtual 3D space.

Abstract: An example method includes capturing, via an x-ray machine, a plurality of x-ray images of a patient covering a number of different anatomy of the patient in any order, using a machine learning algorithm to process the plurality of x-ray images for identification of an anatomy in respective x-ray images of the plurality of x-ray images, associating a label with each of the plurality of x-ray images based on the identification of the anatomy, positioning each of the plurality of x-ray images upright based on a preset coordinate scheme for the anatomy, arranging the plurality of x-ray images into a predetermined order based on the species of the patient, and generating and outputting a data file including the plurality of x-ray images in the predetermined order, positioned upright, and labeled.

Abstract: The invention relates to a method for creating a semantic representation of the environment of a vehicle, having the following steps: acquiring (S1) sensor measuring data by means of at least one first (2a) and/or second environment detection sensor (2b) of the vehicle, detecting (S2) objects and free spaces in the environment of the vehicle, creating (S3) a grid map having occupied and free grid cells based on the detected objects and free spaces; determining (S4) height information by means of the at least one first (2a) and/or second environment detection sensor (2b); adding (S5) the height information to each grid cell; allocating (S6) semantic information to the grid cells based on the height information.