Abstract: A system accesses content structure that includes a first attribute table including a first list of attributes of a first object, and a first mapping including first attribute values. The first list of attributes of the first object also includes a quality attribute indicating a first quality. After a request to modify quality is received, the system searches a plurality of content structures for a suitable second content structure that comprises a second attribute table including a second list of attributes of a second object. The suitable content structure has another attribute that matches a corresponding attribute of the first list of attributes of the first object and a quality attribute indicating a second quality. The system modifies the first attribute table to include the second list of attributes of the second object. In this way content is generated that is of higher or lower quality than the original content.

Abstract: An intelligent police car loudspeaker includes a loudspeaker mechanism composed of a dust cover, a paper cone, a yoke ring, a centering piece, a magnet, a voice coil, and a soft iron core. The voice coil is disposed around the soft iron core. The magnet is disposed around the voice coil. The paper cone is disposed above the magnet. The centering piece is disposed above the magnet and located inside the paper cone. The yoke ring is disposed above the centering piece and located inside the paper cone. The dust cover is configured to cover an opening of the paper cone. With the present invention, the level of intelligence of the loudspeaker can be improved.

Abstract: Provided is a method for reconstructing content image data. The method includes selecting a first point and a second point in a first image of first content, selecting a third point and a fourth point in a second image of second content (the second image is an image corresponding to the first image and the third point and the fourth point are points in an image corresponding to the first point and the second point, respectively), generating a first reference vector using the first point and the second point, generating a second reference vector using the third point and the fourth point, calculating a rotation, scale, and transformation (RST) value from the first image to the second image using the first reference vector and the second reference vector; and reconstructing the second content using the calculated RST value.

Abstract: A system, a method, and a computer program for surveillance and area encroachment detection, including receiving satellite image data containing an image of a geospatial area, extracting features from the satellite image data of an object in the image, classifying the object in the image based on the extracted features, comparing the extracted features of the object to previously extracted features for the geospatial area, determining delta features between the extracted features of the object and the previously extracted features for the geospatial area, determining existence of an alarm event in the geospatial area based on the delta features, and transmitting an alarm event message to a communicating device.

Abstract: Various approaches are disclosed to temporally and spatially filter noisy image data—generated using one or more ray-tracing effects—in a graphically rendered image. Rather than fully sampling data values using spatial filters, the data values may be sparsely sampled using filter taps within the spatial filters. To account for the sparse sampling, locations of filter taps may be jittered spatially and/or temporally. For filtering efficiency, a size of a spatial filter may be reduced when historical data values are used to temporally filter pixels. Further, data values filtered using a temporal filter may be clamped to avoid ghosting. For further filtering efficiency, a spatial filter may be applied as a separable filter in which the filtering for a filter direction may be performed over multiple iterations using reducing filter widths, decreasing the chance of visual artifacts when the spatial filter does not follow a true Gaussian distribution.

Abstract: An object detection device equipped with: a first object detection unit that uses a predetermined prediction model to acquire, from a known first image for which the coordinates of a detection subject are known, a confidence value with respect to each detection region extracted from a plurality of positions in the first image; a parameter determination unit that, on the basis of the acquired confidence value, determines parameters that include a detection threshold value which is a threshold value with respect to the confidence value; and a second object detection unit that uses the prediction model to acquire a confidence value with respect to each detection region extracted from the narrowed-down detection region candidates, and detects the detection subject on the basis of the acquired confidence value.

Abstract: Methods and systems of breaking pursuit of a target. One example embodiment includes an electronic processor configured to develop a first identifier for the target and determine a breaking junction and an intercept point associated with a cornering route. The processor is configured to determine a geographical area associated with at least one possible target flee route for the target and determine a second identifier for an object within the geographical area. The processor is configured to develop a discrimination factor representing a degree of differentiation of the first identifier from the second identifier. The processor is configured to predict whether the discrimination factor will exceed a threshold when the pursuit asset arrives at the breaking junction. The processor is configured to, in response to the discrimination factor exceeding the threshold, notify the pursuit asset to break pursuit of the target at the breaking junction to execute the cornering route.

Abstract: A control device assumes that observation light observed by an imaging device is composite light of primary reflection light and secondary reflection light. The control device acquires three or more samples of a brightness amplitude value of the observation light, calculates a phase error caused by the secondary reflection light using these samples, calculates a corrected phase value by correcting a phase value of the observation light using the phase error, and calculates a three-dimensional position of the measurement point on the measurement object based on the corrected phase value.

Abstract: An information processing method includes the following performed using a computer: acquiring images created through capturing at the same time, and positions and capturing directions of image capturing devices that created respectively each of the images; acquiring object detection results obtained respectively through object detection processes performed using each of the images; and performing a training data selection process using the images, the positions and the capturing directions, and the object detection results acquired. The training data selection process includes: calculating a common region that is seen in the images in common, based on the positions and the capturing directions; determining a degree of agreement among the object detection results in the common region; and selecting an image to be used as training data from among the images, according to the degree of agreement.

Abstract: One embodiment provides a system that facilitates efficient collection of training data for training an image-detection artificial intelligence (AI) engine. During operation, the system obtains a three-dimensional (3D) model of a physical object placed in a scene, generates a virtual object corresponding to the physical object based on the 3D model, and substantially superimposes, in a view of an augmented reality (AR) camera, the virtual object over the physical object. The system can further configure the AR camera to capture a physical image comprising the physical object in the scene and a corresponding AR image comprising the virtual object superimposed over the physical object, and create an annotation for the physical image based on the AR image.

Abstract: Disease detection from medical images is provided. In various embodiments, a medical image of a patient is read. The medical image is provided to a trained anatomy segmentation network. A feature map is received from the trained anatomy segmentation network. The feature map indicates the location of at least one feature within the medical image. The feature map is provided to a trained classification network. The trained classification network was pre-trained on a plurality of feature map outputs of the segmentation network. A disease detection is received from the trained classification network. The disease detection indicating the presence or absence of a predetermined disease.

Abstract: At least some example embodiments disclose a device and a method for generating a synthetic image and a different-angled image and eliminating noise. The method may include receiving input images, extracting feature values corresponding to the input images using an image learning model, the image learning model permitting an input and an output to be identical and generating a synthetic image based on the feature values corresponding to the input images using the image learning model.

Abstract: A method identifying electronic communication components employed for transmitting and receiving electronic communications for subsequent testing thereof is provided which identifies each electronic communication component using a digital photo thereof. Communications characteristics required for communicating with each identified component are discerned using the component identity ascertained from the digital image.

Abstract: There is provided an image processing device that includes a facial organ information detection unit that detects facial organ information which is a position of a facial organ of an object from an input image, a face direction information calculation unit that calculates face direction information of the object from the facial organ information, and an arbitrary face direction image generation unit that generates an image obtained by changing the face direction of the object from the facial organ information and the face direction information, and when it is determined by the face direction information that the face is inclined, the arbitrary face direction image generation unit generates an arbitrary face direction image after conducting a correction on the face direction information based on front facial organ information which is a facial organ arrangement in the front face of the object.

Abstract: There is provided a method and an apparatus for authenticating a liveness face, and a computer program product thereof. The method for authenticating a liveness face may comprises: generating a character string randomly and showing the same to an object to be authenticated; recognizing facial actions of the object to be authenticated; determining whether the facial actions match with pronunciation of the character string to obtain a first determination result; and judging whether the object to be authenticated is a liveness face based on the first determination result.

Abstract: In the conventional art, there has been a problem that it is difficult to perform, with a high usability and at a high precision, authentication that accepts a wide range of variation of showing attitude of a hand or a finger and ensures obtaining a clear blood-vessel image of a finger. Provided is a blood-vessel image capturing apparatus including an opening portion formed in a surface of a housing, plural light sources disposed beside the opening portion and arranged in a lattice pattern, a sensor configured to obtain position information of a hand shown above the opening portion, a light amount control portion configured to select an irradiation light source to irradiate the hand from the plural light sources on a basis of the position information and control a light amount of the irradiation light source, and an image capturing portion configured to capture an image of a blood vessel included in a finger portion of the hand irradiated with light from the irradiation light source.

Abstract: Disclosed herein are methods and systems for classifying pixels as foreground using both short-range depth data and long-range depth data. One embodiment takes the form of a process that includes obtaining video data depicting at least a portion of a user. The process also includes obtaining short-range depth data associated with the video data. The process also includes obtaining long-range depth data associated with the video data. The video data, short-range depth data, and long-range depth data may be obtained via a single 3-D video camera. The process also includes classifying pixels of the video data as foreground based at least in part on both the short-range depth data and the long-range depth data. In some embodiments, classifying pixels of the video data as foreground comprises employing an alpha mask. The alpha mask may comprise binary foreground (hard) indicators. The alpha mask may comprise foreground-likelihood (soft) indicators.

Abstract: Method, device and computer-readable medium for sensitive picture recognition are provided in the disclosure. Aspects of the disclosure provide a method for sensitive picture recognition. The method includes receiving a picture to be processed from a picture library associated with a user account, applying a sensitive picture recognition model to the picture to determine whether the picture is a sensitive picture or not, and providing a privacy protection associated with the user account to the picture when the picture is the sensitive picture. In an example, the method includes storing the picture in a private album under the user account with access security protection.

Abstract: The present invention provides a method and a device for detecting defects in a pressing test of a touch screen. The method for detecting defects in a pressing test of a touch screen includes: Step S1: acquiring, after each test point of the touch screen is tested, an image of a test region in which the test point is located, when performing the pressing test; Step S2: identifying a quantity of abnormal points in the acquired image; and Step S3: comparing the identified quantity of abnormal points with a quantity of abnormal points allowed in the pressing test, and determining that the touch screen has defects if the identified quantity of abnormal points exceeds the quantity of abnormal points allowed in the pressing test. The above method for detecting defects can check instantly and accurately whether defects arise on the touch screen during the pressing test.

Abstract: The present invention is directed at a system, method and device for detecting offensive content on a portable electronic device, by monitoring communications sent, received or stored on the portable electronic device, and wherein monitoring comprises collecting content data, classifying content data by calculating an alert score for content data wherein an alert score corresponds to offensive content detected, and sending an alert notification to a second portable electronic device to alert the detection of offensive content on the first portable electronic device.