Abstract: A method for implementing a self-optimized video analytics pipeline is presented. The method includes decoding video files into a sequence of frames, extracting features of objects from one or more frames of the sequence of frames of the video files, employing an adaptive resource allocation component based on reinforcement learning (RL) to dynamically balance resource usage of different microservices included in the video analytics pipeline, employing an adaptive microservice parameter tuning component to balance accuracy and performance of a microservice of the different microservices, applying a graph-based filter to minimize redundant computations across the one or more frames of the sequence of frames, and applying a deep-learning-based filter to remove unnecessary computations resulting from mismatches between the different microservices in the video analytics pipeline.

Abstract: Methods and systems for face clustering include determining a quality score for each of a set of input images. A first subset of the input images is clustered, having respective quality scores that exceed a predetermined threshold, to form an initial set of clusters. A second subset of the input images is clustered, having respective quality scores below the predetermined threshold. An action is performed responsive to the clustered images after the second subset is added to the initial set of clusters.

Abstract: A method for optimal placement of microservices of a micro-services-based application in a multi-tiered computing network environment employing 5G technology is presented. The method includes accessing a centralized server or cloud to request a set of services to be deployed on a plurality of sensors associated with a plurality of devices, the set of services including launching an application on a device of the plurality of devices, modeling the application as a directed graph with vertices being microservices and edges representing communication between the microservices, assigning each of the vertices of the directed graph with two cost weights, employing an edge monitor (EM), an edge scheduler (ES), an alerts-manager at edge (AM-E), and a file transfer (FT) at the edge to handle partitioning of the microservices, and dynamically mapping the microservices to the edge or the cloud to satisfy application-specific response times.

Abstract: Methods and systems for image clustering include matching a new image to a representative image of a cluster. The new image is set as a representative of the cluster with a first time limit. The new image is set as a representative of the cluster with a second time limit, responsive to a determination that the new image has matched at least one incoming image during the first time limit.

Abstract: A computer-implemented method includes obtaining a usecase specification and a usecase runtime specification corresponding to the usecase. The usecase includes a plurality of applications each being associated with a micro-service providing a corresponding functionality within the usecase for performing a task. The method further includes determining that at least one instance of the at least one of the plurality of applications can be reused during execution of the usecase based on the usecase specification and the usecase runtime specification, and reusing the at least one instance during execution of the usecase.

Abstract: A computer-implemented method executed by at least one processor for person identification is presented. The method includes employing one or more cameras to receive a video stream including a plurality of frames to extract features therefrom, detecting, via an object detection model, objects within the plurality of frames, detecting, via a key point detection model, persons within the plurality of frames, detecting, via a color detection model, color of clothing worn by the persons, detecting, via a gender and age detection model, an age and a gender of the persons, establishing a spatial connection between the objects and the persons, storing the features in a feature database, each feature associated with a confidence value, and normalizing, via a ranking component, the confidence values of each of the features.

Abstract: A method for free flow fever screening is presented. The method includes capturing a plurality of frames from thermal data streams and visual data streams related to a same scene to define thermal data frames and visual data frames, detecting and tracking a plurality of individuals moving in a free-flow setting within the visual data frames, and generating a tracking identification for each individual of the plurality of individuals present in a field-of-view of the one or more cameras across several frames of the plurality of frames. The method further includes fusing the thermal data frames and the visual data frames, measuring, by a fever-screener, a temperature of each individual of the plurality of individuals within and across the plurality of frames derived from the thermal data streams and the visual data streams, and generating a notification when a temperature of an individual exceeds a predetermined threshold temperature.

Abstract: Systems and methods to specify and execute real-time streaming applications are provided. The method includes specifying an application topology for an application including spouts, bolts, connections, a global hash table, and a topology manager. Each spout receives input data and each bolt transforms the input data, the global hash table allows in memory communication between each spout and bolt to others of the spouts and the bolts. The topology manager manages the application topology. The method includes compiling the application into a shared or static library for applications, and exporting a special symbol associated with the application. The runtime system can be used to retrieve the application topology from the shared or static library based on the special symbol and execute the application topology on a single node or distribute across multiple nodes.

Abstract: Systems and methods are disclosed for distributed real-time security monitoring and alerting. The methods include transmitting a selected portion of biometrics data as a watchlist to each worker unit. The portion of biometrics data is selected in response to respective characteristic data received from each worker unit. Facial recognition data is received from each worker unit. The facial recognition data includes a person of interest with an associated match confidence value calculated by each worker unit based on respective watchlists received by each worker unit. A combined match confidence value is calculated between a same person of interest identified in multiple facial recognition data received from each worker unit and the biometric data associated with an individual. The combined match confidence value is calculated in response to match confidence values associated with the same person of interest in respective facial recognition data being below a match confidence threshold.

Abstract: Methods and systems for video analysis and response include detecting face images within video streams. Noisy images are filtered from the detected face images. Batches of the remaining detected face images are clustered to generate mini-clusters, constrained by temporal locality. The mini-clusters are globally clustered to generate merged clusters formed of face images for respective people, using camera-chain information to constrain a set of the video streams being considered. Analytics are performed on the merged clusters to identify a tracked individual's movements through an environment. A response is performed to the tracked individual's movements.

Abstract: A computer-implemented method includes obtaining a usecase specification and a usecase runtime specification corresponding to the usecase. The usecase includes a plurality of applications each being associated with a micro-service providing a corresponding functionality within the usecase for performing a task. The method further includes managing execution of the usecase within a runtime system based on the usecase and usecase runtime specifications to perform the task by serving an on-demand query and dynamically scaling resources based on the on-demand query, including using a batch helper server to employ the usecase specification to load dynamic application instances and connect the dynamic application instances to existing instances, and employ a batch helper configuration to load nodes/machines for execution of the on-demand query.

Abstract: A computer-implemented method executed by at least one processor for detecting tattoos on a human body is presented. The method includes inputting a plurality of images into a tattoo detector, selecting one or more images of the plurality of images including tattoos, extracting, via a feature extractor, tattoo feature vectors from the tattoos found in the one or more images of the plurality of images including tattoos, applying a deep learning tattoo matching model to determine potential matches between the tattoo feature vectors and preexisting tattoo images stored in a tattoo training database, and generating a similarity score between the tattoo feature vectors and one or more of the preexisting tattoo images stored in the tattoo training database.

Abstract: Methods and systems for managing access include detecting a person within a region of interest in a video stream. It is determined that a clear image of the person's face is not available within the region of interest. Tracking information of the person is matched to historical face tracking information for the person in a previously captured frame. The person's face from the previously captured video frame is matched to an authentication list, responsive to detecting the person within the region of interest, to determine that the detected person is unauthorized for access. A response to the determination that the detected person is unauthorized for access is performed.

Abstract: A method is provided for managing applications for sensors. In one embodiment, the method includes loading a plurality of applications and links for communicating with a plurality of sensors on a platform having an interface for entry of a requested use case; and copying a configuration from a grouping of application instances being applied to a first sensor performing in a function comprising of the requested use case. The method may further include applying the configuration for the grouping of application instances to a second set of sensors to automatically conform the plurality of sensors on the platform to perform the requested use case.

Abstract: A computer-implemented method executed by at least one processor for person identification is presented. The method includes employing one or more cameras to receive a video stream including a plurality of frames to extract features therefrom, detecting, via an object detection model, objects within the plurality of frames, detecting, via a key point detection model, persons within the plurality of frames, detecting, via a color detection model, color of clothing worn by the persons, detecting, via a gender and age detection model, an age and a gender of the persons, establishing a spatial connection between the objects and the persons, storing the features in a feature database, each feature associated with a confidence value, and normalizing, via a ranking component, the confidence values of each of the features.

Abstract: A computer-implemented method includes obtaining a usecase specification and a usecase runtime specification corresponding to the usecase. The usecase includes a plurality of applications each being associated with a micro-service providing a corresponding functionality within the usecase for performing a task. The method further includes managing execution of the usecase within a runtime system based on the usecase and usecase runtime specifications to perform the task by serving an on-demand query and dynamically scaling resources based on the on-demand query, including using a batch helper server to employ the usecase specification to load dynamic application instances and connect the dynamic application instances to existing instances, and employ a batch helper configuration to load nodes/machines for execution of the on-demand query.

Abstract: Systems and methods to specify and execute real-time streaming applications are provided. The method includes specifying an application topology for an application including spouts, bolts, connections, a global hash table, and a topology manager. Each spout receives input data and each bolt transforms the input data, the global hash table allows in memory communication between each spout and bolt to others of the spouts and the bolts. The topology manager manages the application topology. The method includes compiling the application into a shared or static library for applications, and exporting a special symbol associated with the application. The runtime system can be used to retrieve the application topology from the shared or static library based on the special symbol and execute the application topology on a single node or distribute across multiple nodes.

Abstract: Systems and methods are disclosed for distributed real-time security monitoring and alerting. The methods include transmitting a selected portion of biometrics data as a watchlist to each worker unit. The portion of biometrics data is selected in response to respective characteristic data received from each worker unit. Facial recognition data is received from each worker unit. The facial recognition data includes a person of interest with an associated match confidence value calculated by each worker unit based on respective watchlists received by each worker unit. A combined match confidence value is calculated between a same person of interest identified in multiple facial recognition data received from each worker unit and the biometric data associated with an individual. The combined match confidence value is calculated in response to match confidence values associated with the same person of interest in respective facial recognition data being below a match confidence threshold.

Abstract: Methods and systems for image clustering include matching a new image to a representative image of a cluster. The new image is set as a representative of the cluster with a first time limit. The new image is set as a representative of the cluster with a second time limit, responsive to a determination that the new image has matched at least one incoming image during the first time limit.

Abstract: A computer-implemented method includes obtaining a usecase specification and a usecase runtime specification corresponding to the usecase. The usecase includes a plurality of applications each being associated with a micro-service providing a corresponding functionality within the usecase for performing a task. The method further includes determining that at least one instance of the at least one of the plurality of applications can be reused during execution of the usecase based on the usecase specification and the usecase runtime specification, and reusing the at least one instance during execution of the usecase.