Abstract: This application describes an AI-powered Cloud-native Network Video Recorder (NVR) apparatus. This apparatus features multiple Power over Ethernet (PoE) ports, processors, computer-readable memories, and firmware implementing a camera-integration module, an Artificial Intelligence (AI) module, and a cloud-access module. The camera-integration module enables efficient connection and video data reception from heterogeneous cameras. The AI module processes the video data, identifying and generating clips of interest, optimizing surveillance efficiency. Finally, the cloud-access module facilitates the uploading of these clips to cloud storage, ensuring accessible and secure data management. This innovative NVR apparatus enables users to deploy a cloud-native video surveillance system using existing camera devices, significantly lowering the cost of adoption.

Abstract: A method for generating and selecting images of objects based on video data and text data includes receiving, at a processor of a video camera system, a video stream including a series of video frames depicting at least one object. A set of at least one classification for the object is generated. Additionally, an image that depicts the object and that includes a cropped portion of a video frame from the series of video frames is generated. A set of at least one index key is generated based on the set of at least one classification, and the image is stored based on the set of at least one index key. The processor receives a signal representing a text input from a user, and the processor performs at least one of (1) retrieval of the image or (2) generation of an alert.

Abstract: Laser safety shutoff or power reduction is disclosed for optically amplified fiber optic links with high transmission power. In an embodiment, a network element includes an amplifier configured to amplify one or more traffic carrying signals that are being transmitted over an optical fiber connected to the network element; a first receiver configured to receive a first monitoring signal that counter propagates over the optical fiber relative to the one or more traffic carrying signals; and circuitry configured to one or more of reduce power of the amplifier and shut off lasers associated with the amplifier, responsive to a loss of signal at the first receiver.

Abstract: Introduced here are surveillance systems and associated approaches for obfuscating biometric identifiers generated by, or available to, those surveillance systems for privacy reasons. In the event that a surveillance system generates a biometric identifier (e.g., by imaging a face of a person entering the premises of an organization), caution must be taken to only share the biometric identifier with individuals as necessary for security reasons. The approaches introduced here allow the privacy of persons being surveilled to be protected. Specifically, a computer program may selectively apply blurring as an impermanent mask to obfuscate each face in a digital image. This approach limits “reidentification” of a given person to those scenarios where her identity must be determined.

Abstract: Laser safety shutoff or power reduction is disclosed for optically amplified fiber optic links with high transmission power. In an embodiment, a network element includes an amplifier configured to amplify one or more traffic carrying signals that are being transmitted over an optical fiber connected to the network element; a first receiver configured to receive a first monitoring signal that counter propagates over the optical fiber relative to the one or more traffic carrying signals; and circuitry configured to one or more of reduce power of the amplifier and shut off lasers associated with the amplifier, responsive to a loss of signal at the first receiver.

Abstract: Introduced here are surveillance systems and associated approaches for obfuscating biometric identifiers generated by, or available to, those surveillance systems for privacy reasons. In the event that a surveillance system generates a biometric identifier (e.g., by imaging a face of a person entering the premises of an organization), caution must be taken to only share the biometric identifier with individuals as necessary for security reasons. The approaches introduced here allow the privacy of persons being surveilled to be protected. Specifically, a computer program may selectively apply blurring as an impermanent mask to obfuscate each face in a digital image. This approach limits “reidentification” of a given person to those scenarios where her identity must be determined.

Abstract: A method for generating and selecting images of objects based on video data and text data includes receiving, at a processor of a video camera system, a video stream including a series of video frames depicting at least one object. A set of at least one classification for the object is generated. Additionally, an image that depicts the object and that includes a cropped portion of a video frame from the series of video frames is generated. A set of at least one index key is generated based on the set of at least one classification, and the image is stored based on the set of at least one index key. The processor receives a signal representing a text input from a user, and the processor performs at least one of (1) retrieval of the image or (2) generation of an alert.

Abstract: A method for monitoring protected regions of a camera view includes receiving, at a processor of a video camera system, a video stream including a series of video frames depicting at least one scene. A background model is identified based on a predefined representation of at least one region of interest associated with the scene. Each of the video frames is compared to the background model, to define an associated binary mask. A persistent change in the at least one region of interest is detected, based on the binary masks, the persistent change having an associated duration that exceeds a predefined threshold. In response to detecting the persistent change, a change notification message including a video file is generated. The method also includes causing display of the change notification message via a user interface and/or causing transmission of the change notification message to a remote compute device.

Abstract: A method for generating cropped images depicting objects captured in video data includes receiving, at a processor of a video camera system, a video stream including a series of video frames depicting an object. A classification for the object is generated, and an occurrence of the object being detected is identified in an additional video frame(s) from the series of video frames. A motion associated with the object is calculated based on the classification and the additional video frame(s). At least one image that depicts the object and includes a cropped portion of a video frame from the series of video frames is generated, along with an associated set of at least one quality score, in response to calculating the motion. The method also includes causing transmission of the at least one image to at least one remote compute device based on the set of at least one quality score.

Abstract: A method includes receiving, at a processor and from a requestor compute device, a request including a representation of at least one video camera from a set of video cameras. In response to receiving the request, a set of at least one video file is generated by retrieving a set of video clips associated with the at least one video camera and the time range. For each of the at least one video camera, a subset of video clips is selected from the set of video clips for that video camera based on a comparison of anomaly scores for that video camera, and concatenating the subsets of video clips to generate the set of at least one video file. The method also includes sending a signal to cause display of at least one video file from the set of at least one video file via the requestor compute device.

Abstract: A method for monitoring protected regions of a camera view includes receiving, at a processor of a video camera system, a video stream including a series of video frames depicting at least one scene. A background model is identified based on a predefined representation of at least one region of interest associated with the scene. Each of the video frames is compared to the background model, to define an associated binary mask. A persistent change in the at least one region of interest is detected, based on the binary masks, the persistent change having an associated duration that exceeds a predefined threshold. In response to detecting the persistent change, a change notification message including a video file is generated. The method also includes causing display of the change notification message via a user interface and/or causing transmission of the change notification message to a remote compute device.

Abstract: A method and related system operations include obtaining a video stream with an image sensor of a camera device, detecting a plurality of target objects by executing a neural network model based on the video stream with a vision processor unit of the camera device. The method also includes generating a plurality of bounding boxes, determining a plurality of character sequences by, for each respective bounding box of the plurality of bounding boxes, performing a set of optical character recognition (OCR) operations to determine a respective character sequence of the plurality of character sequences. The method also includes updating a plurality of tracklets to indicate the plurality of bounding boxes and storing the plurality of tracklets in association with the plurality of character sequences in a memory of the camera device.

Abstract: Introduced here are surveillance systems and associated approaches for obfuscating biometric identifiers generated by, or available to, those surveillance systems for privacy reasons. In the event that a surveillance system generates a biometric identifier (e.g., by imaging a face of a person entering the premises of an organization), caution must be taken to only share the biometric identifier with individuals as necessary for security reasons. The approaches introduced here allow the privacy of persons being surveilled to be protected. Specifically, a computer program may selectively apply blurring as an impermanent mask to obfuscate each face in a digital image. This approach limits “reidentification” of a given person to those scenarios where her identity must be determined.

Abstract: A method and related system operations includes, determining, for each respective frame of a frame sequence, a respective bounding box that surrounds a respective sub-image of the respective frame, determining a respective string and respective confidence values associated with the respective string based on the respective sub-image, updating the tracklet to comprise the respective bounding box based on the respective string and at least one string generated by the object recognition model for a previous frame, and updating a voting table by adding the respective confidence values to the voting table. The method also includes generating an aggregated string based on the voting table by, for a set of positions of the aggregated string, determining a character associated with a maximum confidence value indicated by the voting table and associating the aggregated string with the tracklet in a data structure.

Abstract: Systems and methods are provided for creating a sequence of turn-up processes for amplifiers. A method, according to one implementation, includes determining when a fiber span is initially installed in an optical line system or when an Optical Line Failure (OLF) in the fiber span has recovered. The optical line system includes a first set of amplifiers deployed at an upstream node and a second set of amplifiers deployed at a downstream node, the upstream node connected to the downstream node via the fiber span. In response to determining that the fiber span is initially installed in the optical line system or that an ORL in the fiber span has recovered, the method also includes sending a flag from the upstream node to the downstream node to allow the first set of amplifiers to perform a first turn-up process before the second set of amplifiers perform a second turn-up process.

Abstract: A method and related system operations include obtaining a video stream with an image sensor of a camera device, detecting a plurality of target objects by executing a neural network model based on the video stream with a vision processor unit of the camera device. The method also includes generating a plurality of bounding boxes, determining a plurality of character sequences by, for each respective bounding box of the plurality of bounding boxes, performing a set of optical character recognition (OCR) operations to determine a respective character sequence of the plurality of character sequences. The method also includes updating a plurality of tracklets to indicate the plurality of bounding boxes and storing the plurality of tracklets in association with the plurality of character sequences in a memory of the camera device.

Abstract: Systems and methods are provided for creating a sequence of turn-up processes for amplifiers. A method, according to one implementation, includes determining when a fiber span is initially installed in an optical line system or when an Optical Line Failure (OLF) in the fiber span has recovered. The optical line system includes a first set of amplifiers deployed at an upstream node and a second set of amplifiers deployed at a downstream node, the upstream node connected to the downstream node via the fiber span. In response to determining that the fiber span is initially installed in the optical line system or that an ORL in the fiber span has recovered, the method also includes sending a flag from the upstream node to the downstream node to allow the first set of amplifiers to perform a first turn-up process before the second set of amplifiers perform a second turn-up process.

Abstract: A surveillance system may comprise one or more computing devices and a plurality of robotic surveillance devices. The one or more computing devices may be configured to obtain video data captured by one or more cameras. The one or more computing devices may analyze the video data to identify two or more conditions, and associate results of the identification with respect to the two or more conditions to determine an activity category. The one or more computing device may assign tasks to the plurality of robotic surveillance devices based on the determined activity category. The plurality of robotic surveillance devices may be configured to perform responding actions in response to receiving the tasks.

Abstract: A method detects mechanical equipment parts. The method includes: obtaining an image of a part; extracting a feature from the image using a machine learning model, identifying a type of surface defect on the basis of the feature to obtain an identification result; and determining whether to replace the part on the basis of the identification result and a predetermined standard of the part. The method reduces the difficulty of detecting a part, can accurately identify a surface defect of the part and determine whether the part needs to be replaced, thereby improving the work efficiency, and shortens the time for mechanical equipment to stop operating for maintenance, thus improving the operating efficiency of the mechanical equipment. The method is automatically executed by a computer, thereby avoiding manually checking errors, improving the accuracy of detection results, and thus improving the reliability of operation of the mechanical equipment.

Abstract: An activity recognition system may comprise a local device and a server. The local device may be configured to: obtain a video; determine whether at least one human is present in one or more frames of the video; in response to determining the at least one human present in the video, determine if the at least one human in each of the frames corresponds to the same person; in response to determining that the at least one human in each of the frames corresponds to the same person, determine if the person is a stranger; and in response to determining that the person is not a stranger, transmit at least a portion of the video to the server. The server may be configured to: predict an activity class associated with the person; and trigger an alarm based on the activity class.