Abstract: According to one embodiment, an information processing device includes acquisition means, detection means, and specifying means. The acquisition means acquires image data according to a lost article to which a symbol of a user is attached and identification information according to a group to which the user belongs. The detection means performs analysis set for each item of identification information according to the group with respect to the image data according to the lost article and detects the identification information for identifying the user included in the symbol. The specifying means specifies the user from the identification information detected by the detection means.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving multiple images from a camera, each image of the multiple images representative of a detection of an object within the image. For each image of the multiple images the methods include: determining a set of detected objects within the image, each object defined by a respective bounding box, and determining, from the set of detected objects within the image and ground truth labels, a false detection of a first object. The methods further include determining that a target object threshold is met based on a number of false detections of the first object in the multiple images, generating, based on the number of false detections for the first object meeting the target object threshold, an adversarial mask for the first object, and providing, to the camera, the adversarial mask.

Abstract: The present invention discloses system and method for enhancing an image based on non-local features. The invention includes an end-to-end trainable and guided method including feature extraction block, non-local feature generator and non-local feature enhancement block, to deal with low-level image problem by using the non-local feature concept. The invention also deploys a non-local feature merge block to rectify translated features and improve non-local feature further to finally reconstruct the rectified features to form an enhanced image.

Abstract: Disclosed are a drug evaluation method and apparatus. The drug evaluation method includes acquiring cell images in response to a drug to be evaluated, loading an image processing-based learning model trained so as to predict molar concentrations, outputting molar concentrations of cells corresponding to the cell images by applying the learning model to the acquired cell images, and calculating a drug evaluation value used to evaluate effects of the drug on the cells based on the molar concentrations of the cells corresponding to the cell images output through the learning model.

Abstract: Systems and techniques are described herein for performing optical flow estimation for one or more frames. For example, a process can include determining an optical flow prediction associated with a plurality of frames. The process can include determining a position of at least one feature associated with a first frame and determining, based on the position of the at least one feature in the first frame and the optical flow prediction, a position estimate of a search area for searching for the at least one feature in a second frame. The process can include determining, from within the search area, a position of the at least one feature in the second frame.

Abstract: Behavioral and mental health therapy systems in accordance with several embodiments of the invention include a wearable camera and/or a variety of sensors (accelerometer, microphone, among various other) connected to a computing system including a display, audio output, holographic output, and/or vibrotactile output to automatically recognize social cues from images captured by at least one camera and provide this information to the wearer via one or more outputs such as (but not limited to) displaying an image, displaying a holographic overlay, generating an audible signal, and/or generating a vibration.

Abstract: Systems, methods, and devices are described for monitoring and protecting electronic hardware, data assets, and the facility itself, particularly well-suited to monitoring remote facilities and resources in edge locations, including for determining door state for both equipment and personnel doors, and for determining values of one or more environmental parameters, using optical image analytics. An example system includes one or more edge-located hardware monitoring devices having one or more physical sensors, and custom software distributed across edge, cloud, mobile, and enterprise platforms. An example monitoring device can include an embedded computer, various sensors of different types, one or more cameras, a power supply, and several communication interfaces. All or virtually all sensing and processing capabilities can be integrated into the edge device, which utilizes low-cost sensors and video analytics to monitor the environment.

Abstract: Disclosed are a product inspection method and device, producing system and a computer storage medium. The method comprises: conducting image acquisition on a product assembly line to obtain a production line image; extracting a product image including a product to be inspected from the production line image; extracting an inspection point image in a part inspection area in the product image; inputting the inspection point image into an inspection model to obtain an inspection result; and determining that the product to be inspected in the product image has defects under the condition that the inspection result meets any of the following conditions.

Abstract: Devices, systems, computer program products and computer implemented methods are provided for dynamically assessing a moving object from a sequence of consecutive volumetric image frames of such object, which images are timely separated by a certain time interval, by: identifying in at least one image of the sequence the object of interest; segmenting the object to identify object contour; propagating the object contour as identified to other images of the sequence; and performing dynamic analysis of the object based on the object contour as propagated.

Abstract: Systems and methods are provided performing for low compute depth map generation by implementing acts of obtaining a stereo pair of images of a scene, downsampling the stereo pair of images, generating a depth map by stereo matching the downsampled stereo pair of images, and generating an upsampled depth map based on the depth map using an edge-preserving filter for obtaining at least some data of at least one image of the stereo pair of images.

Abstract: A technique for processing patient-specific image data for computer assisted surgical navigation. A database is provided including multiple first data sets of two- or three-dimensional image data. Each first data set is representative of first shape data or first biometric data of a skin surface of at least one patient. The method further comprises obtaining, by an optical camera system, a second data set of two- or three-dimensional image data of a skin surface of a particular patient and deriving second shape data or second biometric data of the skin surface from the second data set. By comparing the second shape data or second biometric data with the first shape data or the first biometric data of one or more first data sets, a similarity score is calculated. A signal generated based on the similarity score triggers one of selection and de-selection of a first data set.

Abstract: An image recognition method includes: obtaining an image; extracting a target image region corresponding to a target part from the image, wherein the target image region includes a target object; determining a location of the target object in the target image region (i) according to pixel values of pixels in the target image region and a location relationship between the pixels, or (ii) inputting the target image region to a trained segmentation model to obtain the location of the target object in the target image region; and displaying a recognition result of the image, wherein the recognition result indicates the location of the target object in the target image region.

Abstract: A tracking system includes a set of cameras, a kiosk, and a tracking server. The kiosk receives a payment amount from a person. The tracking server extracts features of the person from an image feed received from the set of cameras. The tracking server generates a session identifier that is associated with the payment amount and a unique code. The unique code represents at least one of the payment amount and features of the person. The tracking server sends a message to the kiosk to provide a ticket corresponding to the payment amount and the unique code to the person. The tracking server receives a digital cart associated with the person comprising items and a total cash value of the items. The tracking server concludes a transaction by deducting the total cash value from the payment amount.

Abstract: An imaging device, comprising an image sensor that exposes a subject image and repeatedly outputs image signals resulting from having subjected this subject image to photoelectric conversion at a fixed period, a subject detection circuit in which the image signals are input to a neural network circuit that has learned operation parameters for detecting a specified subject by deep learning, and that detects the specified subject, and a subject association determination circuit for forming associations based on a positional relationship between a subject (whole subject) that has been detected by the subject detection circuit, and parts of the subject, wherein the specified subject is a subject (whole subject) and parts that have been subjected to subject association.

Abstract: A method of detecting a biometric feature with an electronic device and the method includes the following steps. Firstly, a detection region of the electronic device is provided, and the electronic device includes a plurality of first color pixels, a plurality of second color pixels, and a sensor module. Then, a first color light and a second color light are respectively generated by turning on at least a portion of the first color pixels and at least a portion of the plurality of second color pixels in the detection region. Next, a first area and a second area are simultaneously generated by the first color and the second color light, wherein the first area and the second area are overlapped with the detection region, and the sensor module is overlapped with the detection region. Finally, a biometric feature is determined.

Abstract: According to one embodiment, a reading support system includes a processing device. The processing device includes an extractor and a type determiner. The extractor extracts a plurality of regions from a candidate region. The candidate region is a candidate of a region in which a meter is imaged. The regions respectively include a plurality of characters of the meter. The type determiner determines a type of the meter based on positions of the regions.

Abstract: A fingerprint recognition method and terminal device provide authentication by simultaneously collecting fingerprint data when a power-on signal is detected, attempting to match the fingerprint data with preset fingerprint data, and logging in to the terminal device proceeds when the matching succeeds.

Abstract: A detection device includes a plurality of optical sensors arranged in a detection area, a light source configured to emit light that is emitted to an object to be detected and is detected by the optical sensors, and a processor configured to perform processing based on outputs from the optical sensors. The processor is configured to determine, based on the outputs of the respective optical sensors obtained at a cycle of a predetermined period, an optical sensor an output of which is to be employed from among the optical sensors.

Abstract: An in-vehicle monitoring information generation control device includes: an image acquisition unit acquiring an image generated by capturing the inside of an unmanned vehicle; an abnormality determination unit determining whether or not an abnormality is occurring in the unmanned vehicle; an in-vehicle monitoring information generating unit generating in-vehicle monitoring information, with which no passenger in the unmanned vehicle who is captured in the image can be identified, on the basis of the image acquired by the image acquisition unit; and a transmission control unit transmitting the in-vehicle monitoring information generated by the in-vehicle monitoring information generating unit to the outside of the unmanned vehicle in a case where it is determined that no abnormality is occurring in the unmanned vehicle on the basis of a determination result determined by the abnormality determination unit.

Abstract: A fingerprint acquisition device comprising, a space for receiving a finger of a user, a light source configured to emit a illumination light illuminating the space, a camera configured to acquire an image of a fingerprint of the finger, when the finger is received in the space, and, a polarization system configured to polarize the illumination light before the illumination light reaches the space and after the illumination light has passed through the space, and to polarize an ambient light emanating from outside the device and propagating towards the camera, before the ambient light reaches the space, and to polarize the ambient light after the ambient light has passed through the space.