Abstract: The present invention relates to methods, devices and systems for associating consumable data with an assay consumable used in a biological assay. Provided are assay systems and associated consumables, wherein the assay system adjusts one or more steps of an assay protocol based on consumable data specific for that consumable. Various types of consumable data are described, as well as methods of using such data in the conduct of an assay by an assay system. The present invention also relates to consumables (e.g., kits and reagent containers), software, data deployable bundles, computer-readable media, loading carts, instruments, systems, and methods, for performing automated biological assays.

Abstract: A head-mounted device is provided that includes one or more cameras configured to acquire a raw video feed and one or more displays configured to present a passthrough video feed to a user. Generation of the passthrough video feed can involve processing the raw video feed using an image signal processor and auxiliary compute blocks. One or more of the auxiliary compute blocks can be bypassed in response to detecting one or more failures associated with the auxiliary compute blocks. Configured and operated in this way, the head-mounted device can fall back to a more reliable passthrough video feed without having to power cycle the head-mounted device when a failure occurs.

Abstract: An orthopaedic surgical instrument includes a patella trial and drill guide that may be used to both perform a surgical trial of the patellofemoral joint and guide the surgeon in drilling a number of anchor holes in the patella of the patient.

Abstract: A method and system determine a three-dimensional (3D) pose of an object and 3D locations of landmark points of the object by first obtaining a 3D point cloud of the object. 3D surface patches are extracted from the 3D point cloud, and a parametric model is fitted to each 3D surface patch to determine a set of descriptors. A set of correspondences between the set of descriptors and a set of descriptors of patches extracted from 3D point clouds of objects from the same object class with known 3D poses and known 3D locations of landmark points is determined. Then, the 3D pose of the object and 3D locations of the landmark points of the object are estimated from the set of correspondences.

Abstract: A method and system detects actions of an object in a scene by first acquiring a video of the scene as a sequence of images, wherein each image includes pixels, wherein the video is partitioned into chunks. The object in the video is tracked. For each object and each chunk of the video, trajectories of the pixels within a bounding box located over the object are tracked, and cropped trajectories and cropped images for one or more images in the chunk are produced using the bounding box. Then, the cropped trajectories and cropped images are passed to a recurrent neural network (RNN) that outputs a relative score for each action of interest.

Abstract: Anomalies in real time series are detected by first determining a similarity matrix of pairwise similarities between pairs of normal time series data. A spectral clustering procedure is applied to the similarity matrix to partition variables representing dimensions of the time series data into mutually exclusive groups. A model of normal behavior is estimated for each group. Then, for the real time series data, an anomaly score is determined, using the model for each group, and the anomaly score is compared to a predetermined threshold to signal the anomaly.

Abstract: A method detects anomalies in time series data, by first learning a final set of exemplars by summarizing training time series data using a divide-and-conquer procedure. Then, for each window of testing time series data, a distance to a nearest exemplar in the final set of exemplars is determined, wherein the distance is an anomaly score. Finally, an anomaly is signaled when the anomaly score for a window is greater than a threshold.

Abstract: A method and system detects actions of an object in a scene by first acquiring a video of the scene as a sequence of images, wherein each image includes pixels, wherein the video is partitioned into chunks. The object in the video is tracked. For each object and each chunk of the video, trajectories of the pixels within a bounding box located over the object are tracked, and cropped trajectories and cropped images for one or more images in the chunk are produced using the bounding box. Then, the cropped trajectories and cropped images are passed to a recurrent neural network (RNN) that outputs a relative score for each action of interest.

Abstract: Image capturing systems and methods of capturing images, especially in contact prone environments are provided. The image capturing systems includes an optical sensor and output device adapted to receive the electrical signals from optical sensor and transmit a corresponding signal, and a housing retaining the optical sensor and the output device. The housing is adapted to mount to a surface, for example, inside or on top of a helmet, and includes a low profile above the surface and a footprint in contact with the surface. The size of the footprint is selected whereby and impact loads on the housing are minimized or attenuated before being transmitted to the surface to which the housing is mounted. The invention is uniquely applicable to head gear mounting, but may be used on a broad range of article and a broad range of fields.

Abstract: A method and system determine a three-dimensional (3D) pose of an object and 3D locations of landmark points of the object by first obtaining a 3D point cloud of the object. 3D surface patches are extracted from the 3D point cloud, and a parametric model is fitted to each 3D surface patch to determine a set of descriptors. A set of correspondences between the set of descriptors and a set of descriptors of patches extracted from 3D point clouds of objects from the same object class with known 3D poses and known 3D locations of landmark points is determined. Then, the 3D pose of the object and 3D locations of the landmark points of the object are estimated from the set of correspondences.

Abstract: A method and system tracks objects in an environment by acquiring a first sequence of images of the environment with a visible-light camera having a first frame rate and a second sequence of images with a thermal infrared sensor having a second frame rate. The second frame rate is substantially lower than the first frame rate. The objects are tracked in the first sequence of images to obtain tracks. Warm regions in the second sequence of images are detected to obtain detections. The tracks and the detections are aligned spatially and temporally, and verified to determine whether the tracks and detections coincide after the aligning.

Abstract: Anomalies in real time series are detected by first determining a similarity matrix of pairwise similarities between pairs of normal time series data. A spectral clustering procedure is applied to the similarity matrix to partition variables representing dimensions of the time series data into mutually exclusive groups. A model of normal behavior is estimated for each group. Then, for the real time series data, an anomaly score is determined, using the model for each group, and the anomaly score is compared to a predetermined threshold to signal the anomaly.

Abstract: In a sequence of images of a scene acquired by a stationary camera, objects are detected and tracked by determining a first set of candidate foreground regions according to a background model. A second set of candidate foreground regions is determined according to a set of foreground models. Then, candidate foreground regions in the first set and the second set are validated to produce a final set of foreground regions in the image that include the objects.

Abstract: A method detects anomalies in time series data, by first learning a final set of exemplars by summarizing training time series data using a divide-and-conquer procedure. Then, for each window of testing time series data, a distance to a nearest exemplar in the final set of exemplars is determined, wherein the distance is an anomaly score. Finally, an anomaly is signaled when the anomaly score for a window is greater than a threshold.

Abstract: A method and system tracks objects in an environment by acquiring a first sequence of images of the environment with a visible-light camera having a first frame rate and a second sequence of images with a thermal infrared sensor having a second frame rate. The second frame rate is substantially lower than the first frame rate. The objects are tracked in the first sequence of images to obtain tracks. Warm regions in the second sequence of images are detected to obtain detections. The tracks and the detections are aligned spatially and temporally, and verified to determine whether the tracks and detections coincide after the aligning.

Abstract: According to one embodiment of the present disclosure, hardware initialization code and error action information are retrieved from separate storage areas. The hardware initialization code includes code that initializes a device, and also includes placeholders corresponding to actions that are performed when the device fails initialization. Likewise, the error action information describes the actions that are performed when the device fails initialization. The error action information is converted into macros that include lines of code. As such, the error action placeholders are matched to the macros and, in turn, each of the error action placeholders is replaced with the lines of code corresponding to the matched macros.

Abstract: A method detects an anomaly in a discrete manufacturing process (DMP) by first acquiring signals from the DMP. Events are extracted from the signals as a sequence. Then, it is determined whether the sequence is inconsistent with a normal behavior as represented by a log-based ordering relationship table. If true, then an alarm is signaled.

Abstract: A method detects anomalies in time series data by comparing universal features extracted from testing time series data with the universal features acquired from training time series data to determine a score. The universal features characterize trajectory components of the time series data and stochastic components of the time series data. Then, an anomaly is detected if the anomaly score is above a threshold.

Abstract: Image capturing systems and methods of capturing images, especially in contact prone environments are provided. The image capturing systems includes an optical sensor and output device adapted to receive the electrical signals from optical sensor and transmit a corresponding signal, and a housing retaining the optical sensor and the output device. The housing is adapted to mount to a surface, for example, inside or on top of a helmet, and includes a low profile above the surface and a footprint in contact with the surface. The size of the footprint is selected whereby and impact loads on the housing are minimized or attenuated before being transmitted to the surface to which the housing is mounted. The invention is uniquely applicable to head gear mounting, but may be used on a broad range of article and a broad range of fields.

Abstract: According to one embodiment of the present disclosure, hardware initialization code and error action information are retrieved from separate storage areas. The hardware initialization code includes code that initializes a device, and also includes placeholders corresponding to actions that are performed when the device fails initialization. Likewise, the error action information describes the actions that are performed when the device fails initialization. The error action information is converted into macros that include lines of code. As such, the error action placeholders are matched to the macros and, in turn, each of the error action placeholders is replaced with the lines of code corresponding to the matched macros.