Abstract: A signal acquisition apparatus includes a light source that irradiates a living tissue with light and a detector that acquires signals from light returned from the living tissue to generate output data on the basis of the signals. The detector includes circuitry that acquires the signals and characteristic data regarding the signals and generates the output data on the basis of the characteristic data. The circuitry is implemented in a single semiconductor chip. Further, the present technology also provides a signal acquisition system including the signal acquisition apparatus and an analysis unit configured to analyze output data output from the image acquisition apparatus.

Abstract: Provided are an image processing method, a device, and a storage medium, the method comprising: performing human face detection on a first image, and obtaining position information for each human face in the first image, then determining whether the first image conforms to a multi-person composition rule on the basis of the position information of each human face in the first image; and cropping the first image based on the position information of each face in the first image to obtain a processed image, in response to the first image not complying with the multi-person composition rule.

Abstract: To provide an imaging device and an electronic device capable of capturing a motion of a subject at a moment desired by a user in the motions of the subject. A CIS (2), which is an example of an imaging device according to the present disclosure, includes an imaging unit (5), a memory (6), a detection unit (83), and a decision unit (84). The imaging unit (5) continuously captures images of the subject to generate image data. The memory (6) stores image data. The detection units (83) detects motions of the subject based on the image data. The decision unit (84) decides the image data in which the motion of the subject in a direction matching the moving direction of the subject predicted based on the image data has been detected by the detection unit, as image data to be saved in the memory.

Abstract: A hardware accelerator for an object detection network and a method for detecting an object are provided. The present disclosure provides robust object detection that advantageously augments traditional deterministic bounding box predictions with spatial uncertainties for various computer vision applications, such as, for example, autonomous driving, robotic surgery, etc.

Abstract: A device configured to receive a request for processing a digital document that identifies a target data structure. The device is further configured to obtain the digital document and to process the digital document to identify objects within the digital document. The device is further configured to input the digital document into a machine learning model that is configured to output contextual metadata for the digital document based on the digital document. The contextual metadata describes attributes of the identified objects within the digital document. The device is further configured to populate a first subset of entries in the target data structure with identifiers for the objects identified within the digital document and to populate a second subset of entries in the target data structure with the contextual metadata. The device is further configured to send the populated target data structure to the network device.

Abstract: A method for tracking one or more objects in a specific space is provided. The method includes steps of: (a) inputting original images of the specific space taken from camera to an obfuscation network and instructing the obfuscation network to obfuscate the original images to generate obfuscated images such that the obfuscated images are not identifiable as the original images by a human but the obfuscated images are identifiable as the original images by a learning network; (b) inputting the obfuscated images into the learning network, and instructing the learning network to detect obfuscated target objects, corresponding to target objects to be tracked, in the obfuscated images, to thereby output information on the obfuscated target objects; and (c) tracking the obfuscated target objects in the specific space by referring to the information on the obfuscated target objects.

Abstract: An image capture apparatus includes an image capture unit, a communication unit that receives subject information about a subject captured by an external apparatus, and a control unit that controls the image capture apparatus based on a first operation mode in a case where the subject information does not include information about a main subject, or based on a second operation mode in a case where the subject information includes the information about the main subject. The first operation mode is an operation mode of searching for the main subject, and the second operation mode is an operation mode of capturing an image of the subject at an angle of view that is different from an angle of view of the external apparatus.

Abstract: Multimodal systems are provided for managing safety in an industrial environment. The system comprises: (a) a computer vision component for generating a first output data; (b) a real-time locating component for generating a second output data about an object within the industrial environment and a mobile tag device deployed to the object; (c) a LIDAR component for generating a third output data; and (d) an edge computing device connected to the computer vision component, the real-time locating component and the LIDAR component via a local network, and is configured to: (i) receive a data stream including the first output data, the second output data and the third output data, (ii) process the data stream using a machine learning algorithm trained model to generate a safety related result and feedback data, and (iii) deliver the feedback data to the object via the mobile tag device.

Abstract: An example method may include receiving, at a computing device, a digital image associated with a particular media content program, the digital image containing one or more faces of particular people associated with the particular media content program. A computer-implemented automated face recognition program may be applied to the digital image to recognize, based on at least one feature vector from a prior-determined set of feature vectors, one or more of the particular people in the digital image, together with respective geometric coordinates for each of the one or more detected faces. At least a subset of the prior-determined set of feature vectors may be associated with a respective one of the particular people. The digital image together may be stored in non-transitory computer-readable memory, together with information assigning respective identities of the recognized particular people, and associating with each respective assigned identity geometric coordinates in the digital image.

Abstract: A processor-implemented method of tracking a target object includes: extracting a feature from frames of an input image; selecting one a neural network model from among a plurality of neural network models that is provided in advance based on a feature value range, based on a feature value of a target object that is included in the feature of a previous frame among the frames; and generating a bounding box of the target object included in a current frame among the frames, based on the selected neural network model.

Abstract: A monitoring and photographing module includes one primary camera and N secondary cameras. The primary camera and the N secondary cameras are configured to collect images, and a frame rate at which any secondary camera collects an image is less than a frame rate at which the primary camera collects an image. Regions monitored by the N secondary cameras respectively cover N different regions in a region monitored by the primary camera, and a focal length of any secondary camera is greater than a focal length of the primary camera.

Abstract: A method for acquiring a traffic state, an electronic device, a computer-readable storage medium, a roadside device and a cloud control platform are provided. An implementation of the method may include: acquiring monitoring data from at least one camera in a camera group, wherein the at least one camera is capable of shooting object moving states at different road sections or a same road section of a target intersection; determining, based on the monitoring data acquired from each camera in the at least one camera, a moving trajectory of a reference object recorded by the each camera in the at least one camera; then fusing moving trajectories of the reference object to obtain a completed trajectory; and finally predicting an indication state of a signal light on a corresponding road based on a travel direction of the corresponding road, the completed trajectory being located on the corresponding road.

Abstract: There is provided an optical sensor including a pixel matrix and a readout circuit. The pixel matrix includes multiple pixels arranged in a matrix, and each of the multiple pixels outputs temporal difference pixel data. The readout circuit sequentially reads the pixel matrix using a readout block, and performs the hybrid difference calculation on the temporal difference pixel data of pixels within the readout block. Accordingly, the output of the readout circuit is the data accomplishing temporal difference and spatial difference.

Abstract: The present disclosure provides a method and a system for scanning wafer. The system captures a defect image of a wafer, and generates a reference image corresponding to the first defect image based on a reference image generation model. The system generates a defect marked image based on the defect image and the reference image.

Abstract: An image sensor includes a plurality of pixel blocks and a connection unit. The plurality of pixel blocks includes: a diffusion unit to which an electric charge resulting from photoelectric conversion is transferred; and a transistor containing a source electrically connected with the diffusion unit. The connection unit is electrically connected with a drain of the transistor included in each of the plurality of pixel blocks.

Abstract: A photo design smart assistant system for reducing similar photos for display and product design includes a similarity distance computation module that can calculate hash values of images and to calculate similarity distances between the images using at least the hash values, a burst grouping module that can automatically group the images into a burst based at least in part on the similarity distances of the images, wherein at least one image is automatically selected from the burst of images, an intelligent design creation engine that can automatically create a photo product design using the selected image from the burst, and a printing and finishing facility that can automatically make a physical photo product based on the photo product design.

Abstract: Time-series data uncertainty reduction can include generating an initial accumulated signal based on an event classifier prediction score. The event classifier prediction score can be generated by an event predicator based on time-series data and can correspond to a probability that a target event occurs. Signal leakage can be imposed on the initial accumulated signal. Additionally, an alert can be generated in response to determining that the initial accumulated signal is greater than an alert threshold.

Abstract: An information processing apparatus (2000) analyzes a captured image (12) generated by a camera (10) to determine a motion of a person. The camera (10) is a camera that images a display place where an item is displayed. The information processing apparatus (2000) detects a reference position (24) from the captured image (12). The reference position (24) indicates a position of a hand of the person. The information processing apparatus (2000) decides an analysis target region (30) to be analyzed in the captured image (12) using the reference position (24). The information processing apparatus (2000) analyzes the analysis target region (30) to determine the motion of the person.

Abstract: An exemplary aspect is a location estimation system, including: a feature value extraction processing unit that performs feature value extraction processing for extracting a feature value from an input image; and a location estimation processing unit that compares the extracted feature value with map information and performs location estimation processing for estimating a self-location based on a result of the comparison. While the location estimation processing unit is performing the location estimation processing corresponding to an input image input at a predetermined timing, the feature value extraction processing unit performs the feature value extraction processing on an input image input at a timing after the predetermined timing.

Abstract: In a method for selecting pictures from a sequence of pictures of an object in motion, a computerized user device determines, for each picture in the sequence of pictures, a value of a motion feature of the object. Based on analyzing the values of the motion feature of the pictures in the sequence, the device identifies a first subset of pictures from the pictures in the sequence. The device then selects, based on a second selection criterion, a second subset of pictures from the first subset of pictures. The pictures in the second subset are displayed to a user for further selection.