Abstract: A method for updating a coordinate of an annotated point in a digital image due to camera movement is performed by an image processing device, which obtains a current digital image of a scene. The current digital image has been captured by a camera subsequent to movement of the camera relative the scene. The current digital image is associated with at least one annotated point. Each at least one annotated point has a respective coordinate in the current digital image. The method comprises identifying an amount of the movement by comparing position indicative information in the current digital image to position indicative information in a previous digital image of the scene. The previous digital image has been captured prior to movement of the camera. The method comprises updating the coordinate of each at least one annotated point in accordance with the identified amount of movement and a camera homography.

Abstract: Present embodiments pertain to systems, apparatuses, and methods for analyzing and reporting the movements in mechanical structures, inanimate physical structures, machinery, and machine components, including automatically detecting aliased frequencies of a component on the structure which exhibits frequencies higher than the maximum frequency of the FFT spectrum calculated from the acquired data. To automatically detect the presence of aliased frequencies, a second virtually identical recording is acquired using a slightly different sampling rate and this provides the basis for detecting frequencies which are greater than the Nyquist sampling rate of the video recording and calculating the true frequency value of the aliased peaks in the frequency spectrum.

Abstract: Various implementations disclosed herein include devices, systems, and methods for normal estimation using a directional measurement, such as a gravity vector. In various implementations, a device includes a non-transitory memory and one or more processors coupled with the non-transitory memory. In some implementations, a method includes identifying planar surfaces in an environment represented by an image. Each planar surface is associated with a respective orientation. A directional vector associated with the environment is determined. A subset of the planar surfaces that have a threshold orientation relative to the directional vector is identified. For each planar surface in the subset of the planar surfaces, a normal vector for the planar surface is determined based on the orientation of the planar surface and the directional vector.

Abstract: Systems, methods, and computer-readable media are disclosed for context aware verification for sensor pipelines. Autonomous vehicles (AVs) may include an extensive number of sensors to provide sufficient situational awareness to perception and control systems of the AV. For those systems to operate reliably, the data coming from the different sensors should be checked for integrity. To this end, the systems and methods described herein may use contextual clues to ensure that the data coming from the different the sensors is reliable.

Abstract: Machine vision systems and methods for automatically generating machine vision job(s) based on region of interests (ROIs) of digital images are disclosed herein. The systems and methods comprise configuring a machine vision tool for capturing an image ID depicted in training images and labeling each training image to indicate a success or failure status of an object depicted by the training images. Candidate image feature(s) are extracted from the training images for generation of candidate ROI(s). A training set of ROIs are selected from the candidate ROI(s) and are designated as an included or excluded ROIs. The training set of ROIs and the training images are used to train a vision learning model configured to output a machine vision job deployable to an imaging device that implements the machine vision job to detect the success or failure statuses of additional image(s) depicting the object.

Abstract: A motion recognition-based interaction method includes the steps of: providing a first motion image as a reference to a user terminal, obtaining a second motion image of the motion of a user from the user terminal, extracting a reference motion from the first motion image, extracting the user motion from the second motion image, and evaluating the motion state of the user by comparing the reference motion with the user motion, and providing feedback to the user based on the evaluation of the motion state. The feedback includes visual feedback.

Abstract: A dental device tracking method including acquiring, using an imager of a dental device, at least a first image which includes an image of at least one user body portion outside of a user's oral cavity; identifying the at least one user body portion in the first image; and determining, using the at least the first image, a position of the dental device with respect to the at least one user body portion.

Abstract: Embodiments described herein embodiments described herein provide Contrastive Attention-Supervised Tuning (CAST), a training method to fix the visual grounding ability of contrastive SSL methods based on a data augmentation strategy using unsupervised saliency maps. In addition to the contrastive loss that encourages the model to pick the crop that comes from the corresponding image, CAST provides an explicit grounding supervision through a Grad-CAM based attention loss that enforces models to look at the specified object of interest that is common across different crops when making this decision. A new geometric transform is introduced for randomly cropping different views from an input image based on certain constraints derived from a saliency map.

Abstract: An image sleep analysis method and system thereof are disclosed. During sleep duration, a plurality of visible-light images of a body are obtained. Positions of image differences are determined by comparing the visible-light images. A plurality of features of the visible-light images are identified and positions of the features are determined. According to the positions of the image differences and features, the motion intensities of the features are determined. Therefore, a variation of the motion intensities is analyzed and recorded to provide accurate sleep quality.

Abstract: An information processing apparatus according to an embodiment of the present technology includes a detection unit, an estimation unit, and a prediction unit. The detection unit detects a target object from an input image. The estimation unit estimates a posture of the detected target object. The prediction unit predicts an action of the target object on a basis of the estimated posture.

Abstract: An apparatus that supports driving of a vehicle may include a location check device that determines whether the vehicle is located within a circuit area, based on location information of the vehicle, a camera device that obtains an image around the vehicle, and a processor that recognizes a specific object from the obtained image based on whether the vehicle is located within the circuit area, sets a region of interest (ROI) with respect to the specific object, and performs image-processing on the ROI preferentially.

Abstract: The present disclosure provides systems, methods, and computer program products for controlling an object. An example method can comprise (a) obtaining video data of the object and (b) performing motion analysis on the video data to generate modified video data. The method can further comprise (c) using artificial intelligence (AI) to identify a set of features in the modified video data. The set of features may be indicative of a predicted state of the object. The AI may be been trained offline on historical training data. The method can further comprise (d) using the predicted state to determine a control signal and (e) transmitting, in real-time, the control signal to the object to adjust or maintain a state of the object in relation to the predicted state. Operations (a) to (d) can be performed without contacting the object.

Abstract: A method and apparatus for recognizing an imaged information-bearing medium, a computer-readable storage device and a computer device are provided. The method comprising: acquiring a first image of the imaged information-bearing medium; performing text recognition on the first image to acquire a text content of the imaged information-bearing medium; classifying the imaged information-bearing medium to acquire a type of the imaged information-bearing medium; and archiving the text content according to the type.

Abstract: A moving body speed derivation method that causes at least one computer to execute a process, the process includes deriving a reference point in a second moving body region that is an image of a second moving body, from one image capturing the second moving body among a plurality of time-series images captured by an imaging device installed in a first moving body; deriving a position of the second moving body based on a distance between the imaging device and a feature point in the second moving body corresponding to the reference point in the second moving body region; and deriving speed of the second moving body based on a change amount of the position of the second moving body corresponding to the second moving body region included in the plurality of time-series images.

Abstract: There are provided a device that collects operation data from equipment, and an information processing apparatus that detects an anomaly or an omen of an anomaly of the equipment on the basis of anomaly detection models constructed from the operation data, the information processing apparatus including means for collecting the operation data, means for learning anomaly detection models from the operation data, and means for calculating an anomaly score of respective operation data from the operation data and the anomaly detection models, the means for learning an anomaly detection model in which a dispersion of elements is small among the anomaly detection models.

Abstract: An inspection apparatus comprises an obtaining unit configured to obtain first captured images of printed pages, a first setting unit configured to set an inspection region within a selected captured image selected from the first captured images of the respective pages obtained by the obtaining unit, and a second setting unit configured to perform setting performed on the selected captured image for the first captured image of a page decided based on a result of image analysis on the first captured images of the respective pages obtained by the obtaining unit.

Abstract: An information processing apparatus (2000) detects one or more candidate regions (22) from a captured image (20) based on an image feature of a target object. Each candidate region (22) is an image region that is estimated to represent the target object. The information processing apparatus (2000) detects a person region (26) from the captured image (20) and detects an estimation position (24) based on the detected person region (26). The person region (26) is a region that is estimated to represent a person. The estimation position (24) is a position in the captured image (20) where the target object is estimated to be present. Then, the information processing apparatus (2000) determines an object region (30), which is an image region representing the target object, based on each candidate region (22) and the estimation position (24).

Abstract: Systems and methods herein describe using a neural network to identify a first set of joint location coordinates and a second set of joint location coordinates and identifying a three-dimensional hand pose based on both the first and second sets of joint location coordinates.

Abstract: An image processing system having at least one processor configured to: obtain a captured image of a document that includes a fixed part and an un-fixed part, the document being captured by an image reader or an image capture device; detect a feature part of the fixed part based on the captured image; obtain, in a case where the feature part is detected, a shaped image of the captured image such that a positional relationship of the feature part is aligned with a predetermined first positional relationship; and search for, in a case where the feature part is not detected, a substitute feature part of the fixed part based on the captured image, wherein in a case where the feature part is not detected, the at least one processor obtains the shaped image such that a position of the substitute feature part is aligned with a predetermined second position.

Abstract: There is provided a method for detecting a vehicle including receiving continuously captured front images, setting a search area of the vehicle in a target image based on a location of the vehicle or a vehicle area detected from a previous image among the front images, detecting the vehicle in the search area according to a machine learning model, and tracking the vehicle in the target image by using feature points of the vehicle extracted from the previous image according to a vehicle detection result based on the machine learning model. Since the entire image is not used as a vehicle detection area, a processing speed may be increased, and a forward vehicle tracked in an augmented reality navigation may be continuously displayed without interruption, thereby providing a stable service to the user.