Abstract: Disclosed herein are apparatuses and methods for iteratively mapping a layout of an environment. The implementations include receiving a visual stream from a camera installed in the environment, wherein the visual stream depicts a view of the environment, and wherein positional parameters of the camera and dimensions of the environment are set to arbitrary values. The implementations include monitoring a plurality of persons in the visual stream. For each person in the plurality of persons, the implementations further includes identifying a respective path that the person moves along in the view, updating the dimensions of the environment captured in the view, based on an estimated height of the person and movement speed along the respective path, and updating the positional parameters of the camera based on the updated dimensions of the environment. The implementations further includes mapping a layout of the environment captured in the view of the camera.

Abstract: Aspects of the present disclosure provide techniques that utilize artificial intelligence (AI) to preemptively identify and prioritize risks for retailers from shrink loss. Specifically, features of the present disclosure provide actionable prescriptions to prevent shrink based on the output of a hybrid machine learning (ML) system that accurately identifies shrink risk factors and implements a cost-effective shrinkage control plan to reduce the retail theft. The shrinkage control plan may then be displayed to the user on a display device (or user interface) in order to allow for the user (e.g., store manager) to implement the recommendations developed by the recommendation engine.

Abstract: Aspects of the present disclosure provide techniques to implement artificial intelligence (AI) that preemptively identifies and prioritizes risks for retailers for shrink loss. Specifically, features of the present disclosure provide a hybrid machine learning (ML) techniques that selects two or more machine learning algorithms to develop a machine learning model to accurately identify shrink risk factors and implement a cost-effective shrinkage control plan to control the retail theft.

Abstract: Disclosed herein are apparatuses and methods for classifying person type in a visual medium. The implementations include identifying a person in an image, generating a visual boundary around the identified person, and dividing the image into a plurality of image portions such that multiple images portions partially depict the identified person inside the visual boundary. The implementations include generating the divided image on a user interface that prompts a user to select each portion that at least partially depicts a person of a predetermined type. The implementations include receiving a selection of at least one portion. The implementations include generating, for a machine learning model and in response to determining that the selection comprises the identified person, a training input that comprises a training image and a tag indicating that the identified person is of the predetermined type. Additionally, the implementations include storing the training input in memory.

Abstract: Components for an endoscopic vessel harvesting system suitable for harvesting target vessels such as the saphenous vein or radial artery for cardiac artery bypass graft surgery. The main components of such systems include a vessel dissector and a vessel harvester, both of which work in conjunction with a separately provided endoscope. The vessel dissector is an elongated cannula having a blunt tip for separating layers of facial around vessels. The tip may be movable, and is typically transparent to permit viewing forward of the tip using the endoscope. Internal features of the tip may reduce glare back to the endoscope. Several devices improve visibility through the tip by reducing interference from tissue or fluid on the tip. The vessel harvester also has an elongated cannula for receiving the endoscope. Several tools within the harvester permit manipulation, severing, and sealing of vessels forward of the distal end.

Abstract: Disclosed herein are apparatuses and methods for iteratively mapping a layout of an environment. The implementations include receiving a visual stream from a camera installed in the environment, wherein the visual stream depicts a view of the environment, and wherein positional parameters of the camera and dimensions of the environment are set to arbitrary values. The implementations include monitoring a plurality of persons in the visual stream. For each person in the plurality of persons, the implementations further includes identifying a respective path that the person moves along in the view, updating the dimensions of the environment captured in the view, based on an estimated height of the person and movement speed along the respective path, and updating the positional parameters of the camera based on the updated dimensions of the environment. The implementations further includes mapping a layout of the environment captured in the view of the camera.

Abstract: An epicardial clip for reshaping the annulus of the mitral valve of a heart includes a curved member having an anterior segment configured to be positioned in the transverse sinus of the heart, a posterior segment configured to be positioned on the posterior side of the heart, such as on or inferior to the atrioventricular groove, and a lateral segment extending between the anterior segment and the posterior segment. The lateral segment includes a curve such that the first end of the member is positioned at or above the plane of the mitral valve and the second end of the member is positioned at or below the plane of the mitral valve.

Abstract: A system may be configured to perform enhanced detection of occluded objects in a multiple object detection system. In some aspects, the system may determine a first size of a queue captured in a video frame based on an object detection system and a video capture device, and determine a second size of the queue based on the first size of the queue and a correction model. Further, the system may detect a person at a front of the queue based on an object tracking system, determine a first period of time spent by the person at the front of the queue based on an object tracking system, and estimate a second period of time spent in the queue based at least in part on the first period of time and the second size of the queue.

Abstract: Disclosed herein are apparatuses and methods for iteratively mapping a layout of an environment. The implementations include receiving a visual stream from a camera installed in the environment, wherein the visual stream depicts a view of the environment, and wherein positional parameters of the camera and dimensions of the environment are set to arbitrary values. The implementations include monitoring a plurality of persons in the visual stream. For each person in the plurality of persons, the implementations further includes identifying a respective path that the person moves along in the view, updating the dimensions of the environment captured in the view, based on an estimated height of the person and movement speed along the respective path, and updating the positional parameters of the camera based on the updated dimensions of the environment. The implementations further includes mapping a layout of the environment captured in the view of the camera.

Abstract: A system may be configured to implement a probability network for loss prevention sensors. In some aspects, the system may determine a location transition of a tag associated with an article, determine a first predictive value based at least in part on a first predictive structure and the location transition, the first predictive structure corresponding to a valid detection alarm, and determine a second predictive value based at least in part on a second predictive structure and the location transition, the second predictive structure corresponding to an invalid detection alarm. Further, the system may generate a notification based at least in on part on comparing the first predictive value to the second predictive value, the notification indicating unauthorized movement of the tag outside of a geographic area.

Abstract: A system may be configured to accurately track shelf activity in real-time with support for dynamic shelf size, configuration, and item containment. In some aspects, the system may parse regions of a video frame to determine a region of interest representation corresponding to a physical location (e.g., a shelf compartment), determine an enhanced region of interest representation based at least in part on the region of interest representation and an image enhancement pipeline, determine edge information of one or more objects based on the enhanced region of interest representation, compare a reference representation of the physical location to the edge information, and determine the amount of available space for the physical location based on the comparing.

Abstract: A system may be configured to generate real-time analytics using machine learning and computer vision. In some aspects, the system may receive a storage structure video frame and an interaction video frame, determine a storage structure inference based on the storage structure video frame, and determine an interaction inference based on the interaction video frame. Further, the system may determine that the storage structure inference and the interaction inference correspond to a common time period and common location, and generate analytics information based on the storage structure inference and the interaction inference.

Abstract: Disclosed herein are apparatuses and methods for classifying person type in a visual medium. The implementations include identifying a person in an image, generating a visual boundary around the identified person, and dividing the image into a plurality of image portions such that multiple images portions partially depict the identified person inside the visual boundary. The implementations include generating the divided image on a user interface that prompts a user to select each portion that at least partially depicts a person of a predetermined type. The implementations include receiving a selection of at least one portion. The implementations include generating, for a machine learning model and in response to determining that the selection comprises the identified person, a training input that comprises a training image and a tag indicating that the identified person is of the predetermined type. Additionally, the implementations include storing the training input in memory.

Abstract: A system may be configured to reliably identify, track, and collect data on a person of interest. In some aspects, the system may detect a facial representation within an image, generate a bounding box corresponding to the facial representation, determine an enhanced facial representation based at least in part on the bounding box and an image enhancement pipeline, and extract a plurality of facial features from the enhanced facial representation. Further, the system may determine quality information based on the plurality of facial features, determine that the quality information is greater than a threshold, and store the plurality of facial features in a data structure. In some aspects, the facial features may be used to identify red shoppers and green shoppers in a controlled environment.

Abstract: Example aspects include techniques for building a ML model in a use case with prohibitive training data and employing the ML model within the use case. These techniques may include determining training information including a plurality of stray training reads and a plurality of valid training reads, determining modified training information based at least in part on modifying the plurality of valid training reads, and generating a model for distinguishing a valid read from a stray read based on the modified training information and an evolutionary algorithm. In addition, the techniques may include detecting, by a monitoring device, a plurality of tag reads in response to a plurality of interactions between a tag and the monitoring device, and determining, by the monitoring device, a plurality of valid tag reads based on the model and plurality of tag reads.

Abstract: Components for an endoscopic vessel harvesting system suitable for harvesting target vessels such as the saphenous vein or radial artery for cardiac artery bypass graft surgery. The main components of such systems include a vessel dissector and a vessel harvester, both of which work in conjunction with a separately provided endoscope. The vessel dissector is an elongated cannula having a blunt tip for separating layers of facial around vessels. The tip may be movable, and is typically transparent to permit viewing forward of the tip using the endoscope. Internal features of the tip may reduce glare back to the endoscope. Several devices improve visibility through the tip by reducing interference from tissue or fluid on the tip. The vessel harvester also has an elongated cannula for receiving the endoscope. Several tools within the harvester permit manipulation, severing, and sealing of vessels forward of the distal end.

Abstract: Components for an endoscopic vessel harvesting system suitable for harvesting target vessels such as the saphenous vein or radial artery for cardiac artery bypass graft surgery. The main components of such systems include a vessel dissector and a vessel harvester, both of which work in conjunction with a separately provided endoscope. The vessel dissector is an elongated cannula having a blunt tip for separating layers of facial around vessels. The tip may be movable, and is typically transparent to permit viewing forward of the tip using the endoscope. Internal features of the tip may reduce glare back to the endoscope. Several devices improve visibility through the tip by reducing interference from tissue or fluid on the tip. The vessel harvester also has an elongated cannula for receiving the endoscope. Several tools within the harvester permit manipulation, severing, and sealing of vessels forward of the distal end.

Abstract: A system for generating a false alarm rule for preventing a false alarm that occurs at a building includes a processing circuit configured to receive, via a communications interface, building data including events for the building devices. The building events include a first non-alarm event, a second non-alarm event different than the first non-alarm event, and a false alarm event. The processing circuit is configured to generate an event sequence based on the events, where the event sequence includes the first non-alarm event and the second non-alarm event and indicates a relationship between the first non-alarm event and the second non-alarm event that is indicative of a situation at the building that causes the false alarm event to occur. The processing circuit is configured to generate the false alarm rule based on the event sequence. The false alarm rule includes a recommendation for preventing the false alarm event from occurring.

Abstract: Systems and methods for identifying at risk building sites. The security system includes a processing circuit configured to receive building security data from the plurality of building sites, the building security data indicating one or more vulnerability time periods for each of the plurality of building sites and determine an average vulnerability time period associated with each of the plurality building sites based on the one or more vulnerability time periods. The processing circuit can also be configured to determine a tunable threshold associated with the average vulnerability time period; determine whether each of the plurality of building sites are at risk by determining whether a current vulnerability time period for each building site is greater than the tunable threshold associated with the average vulnerability time period; and generate a report indicating one or more of the plurality of building sites that are at risk.

Abstract: Systems and methods for reducing false alarms of a building are disclosed. The system includes a processing circuit configured to receive building security data of the building, the building security data comprising one or more events and identify a plurality of satisfied rules of a plurality of rules based on the one or more events, wherein each of the plurality of rules is associated with a particular sequence of one or more particular events. The processing circuit is also configured to select one satisfied rule of the plurality of satisfied rules based on a rule hierarchy, wherein the rule hierarchy indicates a classification level of each of the plurality of satisfied rules and generate a recommendation for reducing a false alarm associated with the one satisfied rule, wherein the recommendation comprises an indication of a root cause of the false alarm.