Abstract: Methods, systems, and computer-readable media for producing a privacy-protected video stream are described herein. A request to display a live video stream of a camera is received. The live video stream is received in real-time and comprises a plurality of live image frames from the camera. An archived video stream of the camera is accessed in a data repository. A plurality of archived image frames of the archived video stream is processed to generate a background model comprising imagery common to multiple ones of the plurality of archived image frames. The plurality of archived image frames occurring in time prior to the request to display the live video stream. The privacy-protected video stream is processed in real-time. The privacy-protected video stream is output for display.

Abstract: Producing a privacy-protected video clip in a video management system includes retrieving a selected video clip constituting at least a portion of a stored video stream; obtaining segments of the video clip which are spaced apart in time and have a total length equal to a defined time period; combining the obtained segments of the video clip to form a background training clip; and processing the background training clip, or the separate segments, to produce a background model. The video clip is processed to produce a privacy-protected video clip, such that, for each image the video clip, the processing includes performing background subtraction, using the background model, to define foreground regions, and obscuring the defined foreground regions.

Abstract: Computer-implemented systems and methods for video content analysis are described herein. A video feed comprising at least one image captured by a camera is received. The at least one image has a plurality of regions associated with a different level of precision required for each region. An adjustable image processing algorithm is applied to each region of the at least one image to obtain for each region the different level of precision. The image processing algorithm is adjusted based of the different level of precision associated with each region. Meta data indicative of content of the video feed is generating by the image processing algorithm.

Abstract: Producing a privacy-protected video clip in a video management system includes retrieving a selected video clip constituting at least a portion of a stored video stream; obtaining segments of the video clip which are spaced apart in time and have a total length equal to a defined time period; combining the obtained segments of the video clip to form a background training clip; and processing the background training clip, or the separate segments, to produce a background model. The video clip is processed to produce a privacy-protected video clip, such that, for each image the video clip, the processing includes performing background subtraction, using the background model, to define foreground regions, and obscuring the defined foreground regions.

Abstract: Producing a privacy-protected video clip in a video management system includes retrieving a selected video clip constituting at least a portion of a stored video stream; obtaining segments of the video clip which are spaced apart in time and have a total length equal to a defined time period; combining the obtained segments of the video clip to form a background training clip; and processing the background training clip, or the separate segments, to produce a background model. The video clip is processed to produce a privacy-protected video clip, such that, for each image the video clip, the processing includes performing background subtraction, using the background model, to define foreground regions, and obscuring the defined foreground regions.

Abstract: Computer-implemented systems and methods for video content analysis are described herein. A video feed comprising at least one image captured by a camera is received. The at least one image has a plurality of regions associated with a different level of precision required for each region. An adjustable image processing algorithm is applied to each region of the at least one image to obtain for each region the different level of precision. The image processing algorithm is adjusted based of the different level of precision associated with each region. Meta data indicative of content of the video feed is generating by the image processing algorithm.

Abstract: In some embodiments, an apparatus includes a memory and a processor. The processor is configured to receive a set of images associated with a video recorded by a moving or a non-moving camera. The processor is configured to detect a structure of a region of interest from a set of regions of interest in an image from the set of images. The processor is configured to classify the structure into a geometric class from a set of predefined geometric classes using machine learning techniques. The processor is configured to alter the region of interest to generate an altered image when the geometric class is associated with an identity of a person, such that privacy associated with the identity of the person is protected. The processor is configured to send the altered image to a user interface or store the altered image in a standardized format.

Abstract: In some embodiments, an apparatus includes a memory and a processor. The processor is configured to receive a set of images associated with a video recorded by a moving or a non-moving camera. The processor is configured to detect a structure of a region of interest from a set of regions of interest in an image from the set of images. The processor is configured to classify the structure into a geometric class from a set of predefined geometric classes using machine learning techniques. The processor is configured to alter the region of interest to generate an altered image when the geometric class is associated with an identity of a person, such that privacy associated with the identity of the person is protected. The processor is configured to send the altered image to a user interface or store the altered image in a standardized format.

Abstract: In some embodiments, an apparatus includes a memory and a processor. The processor is configured to receive a set of images associated with a video recorded by a moving or a non-moving camera. The processor is configured to detect a structure of a region of interest from a set of regions of interest in an image from the set of images. The processor is configured to classify the structure into a geometric class from a set of predefined geometric classes using machine learning techniques. The processor is configured to alter the region of interest to generate an altered image when the geometric class is associated with an identity of a person, such that privacy associated with the identity of the person is protected. The processor is configured to send the altered image to a user interface or store the altered image in a standardized format.

Abstract: In some embodiments, an apparatus includes a memory and a processor. The processor is configured to receive a set of images associated with a video recorded by a moving or a non-moving camera. The processor is configured to detect a structure of a region of interest from a set of regions of interest in an image from the set of images. The processor is configured to classify the structure into a geometric class from a set of predefined geometric classes using machine learning techniques. The processor is configured to alter the region of interest to generate an altered image when the geometric class is associated with an identity of a person, such that privacy associated with the identity of the person is protected. The processor is configured to send the altered image to a user interface or store the altered image in a standardized format.

Abstract: In some embodiments, an apparatus includes a memory and a processor. The processor is configured to receive a set of images associated with a video recorded by a moving or a non-moving camera. The processor is configured to detect a structure of a region of interest from a set of regions of interest in an image from the set of images. The processor is configured to classify the structure into a geometric class from a set of predefined geometric classes using machine learning techniques. The processor is configured to alter the region of interest to generate an altered image when the geometric class is associated with an identity of a person, such that privacy associated with the identity of the person is protected. The processor is configured to send the altered image to a user interface or store the altered image in a standardized format.