Abstract: A system and method for detecting deviations in building structures over time is disclosed. The system and method use range images of buildings captured using range imaging cameras (for example, time-of-flight cameras) to construct 3D models with sufficient resolution to detect deviations in structures that may not be obvious from looking at only photographic images. The system can also use augmented reality to project parts of a 3D model over photographic images of a structure to facilitate easy inspection of the structure.

Abstract: A weight estimation unit estimates, from a person's image in which a person is included, a weight of a human body part of the person in accordance with an existence probability of the human body part of the person. A feature creation unit creates a feature for verification based on a weight of the person's image and a weight estimated by the weight estimation unit. A verification feature storage unit stores a feature of the person who is the object of verification as a verification feature. A person verification unit compares the feature for verification created by the feature creation unit and the verification feature stored in the verification feature storage unit.

Abstract: Certain aspects provide a method of generating a physical activity model, including: receiving, via a motion capture device, motion data corresponding to a plurality of key states associated with a physical activity sequence; for each respective key state in the plurality of key states: determining a plurality of joint positions associated with the respective key state; determining a plurality of body segment positions associated with the respective key state based on the plurality of joint positions; determining a plurality of inter-state differentiation variables for the respective key state; determining one or more state characteristic metrics for the respective key state; and determining a classifier for the respective key state based on the one or more state characteristic metrics; and defining a physical activity model based on the one or more state characteristic metrics and the classifier associated with each key state.

Abstract: A first computing device broadcasts a first audio token comprising the first user computing device identifier over two or more audio frequency channels at specified intervals and listens for audio inputs via the two or more audio frequency channels at the specified intervals. The first computing device receives a second audio token generated by a second computing device and communicates the received second audio token to the one or more computing devices. The second computing device receives the first audio token generated by the first computing device and communicates the received first audio token to the one or more computing devices. The one or more computing devices receive the first and second audio tokens and pair the first computing device and the second computing device and facilitate a transfer of data between the first computing device and the second computing device.

Abstract: A distance measuring device according to an embodiment includes a first device including a first transceiver configured to transmit a first known signal and a second known signal and receive a third known signal corresponding to the first known signal and a fourth known signal corresponding to the second known signal, a second device including a second transceiver configured to transmit the third known signal and the fourth known signal and receive the first and second known signals and a calculating section configured to calculate a distance between the first device and the second device on a basis of phases of the first to fourth known signals, and the first transceiver and the second transceiver transmit/receive the first and third known signals one time each and transmit/receive the second and fourth known signals one time each, performing transmission/reception a total of four times.

Abstract: A weight estimation unit estimates, from a person's image in which a person is included, a weight of a human body part of the person in accordance with an existence probability of the human body part of the person. A feature creation unit creates a feature for verification based on a weight of the person's image and a weight estimated by the weight estimation unit. A verification feature storage unit stores a feature of the person who is the object of verification as a verification feature. A person verification unit compares the feature for verification created by the feature creation unit and the verification feature stored in the verification feature storage unit.

Abstract: In one aspect, a method for determining soil clods within a field includes receiving one or more images depicting an imaged portion of an agricultural field. The method also includes classifying a portion of the plurality of pixels that are associated with soil within the imaged portion of the field as soil pixels with each soil pixel being associated with a respective pixel height. The method also includes generating a first ray from a local maximum in a first direction and a second ray from the local maximum in a second direction that is perpendicular to the first ray until opposing endpoints are determined based on a detected edge condition. Lastly, the method includes determining whether a soil clod based at least in part the first ray or the second ray of the candidate soil clod.

Abstract: A system performs optical character recognition (OCR) on an image displaying a portion of an object. An image classification system identifies the object in the image, based on which one or more object detection models identify labels associated with the object within the image. The system determines text of the identified labels using OCR, and analyzes the OCR resultant text for discrepancies and/or inaccuracies. In response to identifying a discrepancy, the system provides a recommendation for improving the accuracy of the OCR resultant text.

Abstract: Apparatus and methods for signal boosters for vehicles are provided. In certain embodiments, a vehicle signal booster system includes an interior unit including a mobile station antenna that receives an RF uplink signal and transmits a boosted RF downlink signal. The vehicle signal booster system further includes a top unit including a base station antenna that receives an RF downlink signal and transmits a boosted RF uplink signal. The vehicle signal booster system further includes booster circuitry that generates the boosted RF downlink signal based on amplifying one or more downlink channels of the RF downlink signal, and that generates the boosted RF uplink signal based on amplifying one or more uplink channels of the RF uplink signal. The booster circuitry is implemented in the top unit or in the top unit and the interior unit.

Abstract: A method of instance segmentation in an image and a system for instance segmentation of images. The method includes identifying, with a processor, a starting pixel associated with an object in an image, the image having a plurality of rows of pixels, the starting pixel located in a row of the plurality of rows; identifying, with the processor, at least one pixel located in an adjacent row to the row in which the starting pixel is located, the at least one pixel being part of the same object as the starting pixel; iterating the previous two identification steps using the at least one identified adjacent row pixel as a start pixel for the next iteration; and connecting, with the processor, the at least one identified adjacent row pixels to form polylines representing the object.

Abstract: Apparatus and methods for extraction and calculation of multi-person performance metrics in a three-dimensional space. An example apparatus includes a detector to identify a first subject in a first image captured by a first image capture device based on a first set of two-dimensional kinematic keypoints in the first image, the two-dimensional kinematic keypoints corresponding to a joint of the first subject, the first image capture device associated with a first view of the first subject, a multi-view associator to verify the first subject using the first image and a second image captured by a second image capture device, the second image capture device associated with a second view of the first subject, the second view different than the first view, and a keypoint generator to generate three-dimensional keypoints for the first subject using the first set of two-dimensional kinematic keypoints.

Abstract: A handheld countermeasure device is disclosed herein. The device can include a hand-held form factor body. The device can include disruption components, a directional antenna, and a processor. The disruption components can be configured to generate a disruptive signal. The directional antenna can be configured to emit the disruptive signal. The processor can be configured to determine a position of the handheld countermeasure device based on a global navigation satellite system (GNSS) signal. The processor can be configured to load a device profile for the handheld countermeasure device based on the position of the handheld countermeasure device.

Abstract: A process mining system performs process mining using visual logs generated from video streams of worker devices. Specifically, for a given worker device, the process mining system obtains a series of images capturing a screen of a worker device while the worker device processes one or more tasks related to an operation process. The process mining system determines activity labels for a plurality of images. An activity label for an image may indicate an activity performed on the worker device when the image was captured. The activity label is determined by extracting information from pixels of the image and inferring the activity of the worker device from the extracted information. The process mining system generates event logs from the visual logs of worker devices and uses the event logs for process mining.

Abstract: Systems and methods for analyzing image data to identify cabinet products are disclosed. A computer-implemented method may include receiving, from an electronic device via a network connection, at least one digital image depicting a cabinet. The method also may include analyzing, by one or more processors, the at least one digital image to determine a first set of characteristics of the cabinet. Additionally, the method may include accessing, by the one or more processors from memory, a second set of characteristics corresponding to a plurality of cabinet products and comparing the first set of characteristics to the second set of characteristics to identify a cabinet product of the plurality of cabinet products that matches the cabinet. Further, the method may include transmitting, to the electronic device via the network connection, an indication of the cabinet product.

Abstract: An apparatus includes a memory and a processor. The memory may be configured to store image data of an input image.

Abstract: Disclosed is a method and apparatus for face detection using an adaptive threshold. The method includes determining a detection box in an input image, calculating a confidence score indicating whether an object in the detection box corresponds to a face, setting an adaptive threshold based on a size of the detection box, and determining whether the object in the detection box corresponds to a face based on comparing the confidence score to the adaptive threshold.

Abstract: A computer-implemented method of validating motion correction of magnetic resonance (MR) images in a quantitative parametric map of a parameter is provided. The method includes receiving a series of motion corrected images of a series of MR images, wherein the series of MR images are MR images of an anatomical region at different points of time. For each pixel of a plurality of pixels in one of the series of motion corrected images, the method further includes generating a time series at the pixel based on the series of motion corrected images, fitting the time series to a model of the parameter, and estimating an indicator of goodness of fit of the time series to the model. The method also includes generating a metric indicating effectiveness of the motion correction based on estimated indicators of goodness of fit of the plurality of pixels, and validating the motion correction based on the metric.

Abstract: An automated rack imaging system is provided, including an automated guided vehicle having a housing and a propulsion system configured to move the housing. The automated rack imaging system may include an imaging system coupled to the housing. The imaging system may include a plurality of cameras. The cameras each may be configured to have a respective field of view. The fields of view may be at least partially non-overlapping with one another. The automated rack imaging system may also include an image processor configured to combine a plurality of images taken by the cameras into a single mosaic image. A method of imaging a datacenter rack with the automated guided vehicle is also provided. The method may include moving the automated guided vehicle to a first target location aligned with the datacenter rack, taking the plurality of images, and combining the plurality of images into the single mosaic image.

Abstract: A communication system that includes a base unit and one or more end units that communicate over a primary communication link using a first communication protocol and a secondary communication link using a second protocol. The secondary communication link may be a shorter range communication link than the primary communication link. The secondary communication link may be used to transmit and receive registration information, configuration settings, and status information between the end units and the base unit.

Abstract: An information processing device that receives, from each of several vehicles, both image information captured by an image capture device installed at the vehicle, and vehicle information including position information on the vehicle; performs image processing identifying a characteristic of a dangerously-driven vehicle based on the image information; and in a case in which a dangerously-driven vehicle has been detected, modifies a priority level for image processing of the image information received from another vehicle in the vicinity of a vehicle that has detected the dangerously-driven vehicle, so as to be higher than for a vehicle not in the vicinity of the vehicle that has detected the dangerously-driven vehicle.