Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for storing facial recognition image data in a cache. One of the methods includes receiving an image from a camera, detecting, in the received image, a face of a person, searching a biometric data cache based on the detected face, in response to searching the biometric data cache based on the detected face, determining whether the biometric data cache includes data for the person, in response to a determination that the biometric data cache includes data for the person, using the data from the biometric data cache to determine an identifier for the person, and in response to a determination that the biometric data cache does not include data for the person: searching a data storage system based on the detected face of the person to determine whether the data storage system includes data for the person.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for tracking objects over a sequence of images. In one aspect, a process includes receiving data specifying visual attributes of a particular object detected in an image. Data specifying visual attributes of a tracked object is identified. A level of similarity is determined between the particular object and the tracked object based on comparison of visual attributes of the particular object with corresponding visual attributes of the tracked object. A first normalization function is used to normalize a level of similarity between first corresponding visual attributes of the particular object and the tracked object. A second normalization function is used to normalize a level of similarity between second corresponding visual attributes of the particular object and the tracked object. A determination is made, based on the level of similarity, whether the particular object matches the tracked object.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for storing facial recognition image data in a cache. One of the methods includes receiving an image from a camera, detecting, in the received image, a face of a person, searching a biometric data cache based on the detected face, in response to searching the biometric data cache based on the detected face, determining whether the biometric data cache includes data for the person, in response to a determination that the biometric data cache includes data for the person, using the data from the biometric data cache to determine an identifier for the person, and in response to a determination that the biometric data cache does not include data for the person: searching a data storage system based on the detected face of the person to determine whether the data storage system includes data for the person.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for storing facial recognition image data in a cache. One of the methods includes receiving an image from a camera, detecting, in the received image, a face of a person, searching a biometric data cache based on the detected face, in response to searching the biometric data cache based on the detected face, determining whether the biometric data cache includes data for the person, in response to a determination that the biometric data cache includes data for the person, using the data from the biometric data cache to determine an identifier for the person, and in response to a determination that the biometric data cache does not include data for the person: searching a data storage system based on the detected face of the person to determine whether the data storage system includes data for the person.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for tracking objects over a sequence of images. In one aspect, a process includes receiving data specifying visual attributes of a particular object detected in an image. Data specifying visual attributes of a tracked object is identified. A level of similarity is determined between the particular object and the tracked object based on comparison of visual attributes of the particular object with corresponding visual attributes of the tracked object. A first normalization function is used to normalize a level of similarity between first corresponding visual attributes of the particular object and the tracked object. A second normalization function is used to normalize a level of similarity between second corresponding visual attributes of the particular object and the tracked object. A determination is made, based on the level of similarity, whether the particular object matches the tracked object.

Abstract: This document describes systems, methods, devices, and other techniques for accessing a first video showing a first two-dimensional scene of an environment and captured by a first camera located in the environment having a first field of view; detecting one or more objects shown in the first video; analyzing the first video to determine one or more features of each of the detected objects shown in the first video; accessing a second video showing a second 2D scene of the environment and captured by a second camera located in the environment having a second field of view; detecting one or more objects shown in the second video; analyzing the second video to determine one or more features of each of the detected objects shown in the second video; and correlating one or more objects shown in the first video with one or more objects shown in the second video.

Abstract: Virtual access control may include detecting entry of a person into a virtual controlled zone, and counting and/or identifying people including the person entering into the virtual controlled zone. Virtual access control may further include determining an authorization of the person to continue through the virtual controlled zone based on a facial identification of the person, and alerting the person to stop, exit from, or continue through the virtual controlled zone based on the determined authorization. An alarm may be generated if the person violates directions provided by the alert.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for identifying people depicted in images. In one aspect, a process includes receiving an image from a camera. A face of a person is detected in the image. The image is compared to a set of images stored in a local cache. A determination is made whether the face of the person matches a face of a person depicted by at least one image of the set of images. In response to determining that the face of the person does not match a face of a person depicted by at least one image of the set of images, a selection is made of a highest quality image of the face of the person. A server system compares the highest quality image to images from data for the multiple people to identify the person.

Abstract: Computerized methods and systems, including computer programs encoded on a computer storage medium, may detect event shown within digital video content captured by one or more video cameras, and correlate these detected events to real-world conditions that may not be captured within the digital video data. For example, a computing system may detect events shown within digital video content captured by one or more video cameras, and may obtain data that identifies at least one external event. The computer system may establish a predictive model that correlates values of event parameters that characterize the detected and external events during a first time period, and may apply the predictive model to an event parameter that characterizes an additional event detected during a second time period. Based on an outcome of the predictive model, the computing system may determine an expected value of the external event parameter during the second time period.

Abstract: This document describes systems, methods, devices, and other techniques for video camera self-calibration based on video information received from the video camera. In some implementations, a computing device receives video information characterizing a video showing a scene from a field of view of a video camera; detects an object that appears in the scene of the video; identifies a visual marking that appears on the detected object; determines a particular visual marking among a plurality of pre-defined visual markings that matches the visual marking that appears on the detected object; identifies one or more object characteristics associated with the particular visual marking; evaluates one or more features of the video with respect to the one or more object characteristics; and based on a result of evaluating the one or more features of the video with respect to the one or more object characteristics, sets a parameter of the video camera.

Abstract: This document describes systems, methods, devices, and other techniques for video camera scene translation. In some implementations, a computing device accesses a first video that shows a first 2D scene of an environment; defines a trip wire at a first position of the first 2D scene; obtains a 3D model of at least a portion of the environment shown in the first 2D scene; maps the trip wire from the first position of the first 2D scene to a first position of the 3D model that corresponds to the first position of the first 2D scene; accesses a second video that shows a second 2D scene of the environment; and projects the trip wire from the first position of the 3D model to a first position of the second 2D scene that corresponds to a same location in the environment as the first position of the first 2D scene.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for storing facial recognition image data in a cache. One of the methods includes receiving an image from a camera, detecting, in the received image, a face of a person, searching a biometric data cache based on the detected face, in response to searching the biometric data cache based on the detected face, determining whether the biometric data cache includes data for the person, in response to a determination that the biometric data cache includes data for the person, using the data from the biometric data cache to determine an identifier for the person, and in response to a determination that the biometric data cache does not include data for the person: searching a data storage system based on the detected face of the person to determine whether the data storage system includes data for the person.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for identifying people depicted in images. In one aspect, a process includes receiving an image from a camera. A face of a person is detected in the image. The image is compared to a set of images stored in a local cache. A determination is made whether the face of the person matches a face of a person depicted by at least one image of the set of images. In response to determining that the face of the person does not match a face of a person depicted by at least one image of the set of images, a selection is made of a highest quality image of the face of the person. A server system compares the highest quality image to images from data for the multiple people to identify the person.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for storing facial recognition image data in a cache. One of the methods includes receiving an image from a camera, detecting, in the received image, a face of a person, searching a biometric data cache based on the detected face, in response to searching the biometric data cache based on the detected face, determining whether the biometric data cache includes data for the person, in response to a determination that the biometric data cache includes data for the person, using the data from the biometric data cache to determine an identifier for the person, and in response to a determination that the biometric data cache does not include data for the person: searching a data storage system based on the detected face of the person to determine whether the data storage system includes data for the person.

Abstract: Computerized methods and systems, including computer programs encoded on a computer storage medium, may detect event shown within digital video content captured by one or more video cameras, and correlate these detected events to real-world conditions that may not be captured within the digital video data. For example, a computing system may detect events shown within digital video content captured by one or more video cameras, and may obtain data that identifies at least one external event. The computer system may establish a predictive model that correlates values of event parameters that characterize the detected and external events during a first time period, and may apply the predictive model to an event parameter that characterizes an additional event detected during a second time period. Based on an outcome of the predictive model, the computing system may determine an expected value of the external event parameter during the second time period.

Abstract: Impact time between an image sensing circuitry and an object relatively moving at least partially towards, or away from, the image sensing circuitry can be computed. Image data associated with a respective image frame of a sequence (1 . . . N) of image frames sensed by said image sensing circuitry and which image frames are imaging said object can be received. For each one (i) of multiple pixel positions, a respective duration value (f(i)) indicative of a largest duration of consecutively occurring local extreme points in said sequence (1 . . . N) of image frames can be computed. A local extreme point is present in a pixel position (i) when an image data value of the pixel position (i) is a maxima or minima in relation to image data values of those pixel positions that are closest neighbors to said pixel position (i).

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for identifying people depicted in images. In one aspect, a process includes receiving an image from a camera. A face of a person is detected in the image. The image is compared to a set of images stored in a local cache. A determination is made whether the face of the person matches a face of a person depicted by at least one image of the set of images. In response to determining that the face of the person does not match a face of a person depicted by at least one image of the set of images, a selection is made of a highest quality image of the face of the person. A server system compares the highest quality image to images from data for the multiple people to identify the person.

Abstract: Method and an imaging and processing circuit for identifying a certain pixel as a local extreme point. The imaging and processing circuit generates, in a certain sensing element associated with said certain pixel and in two or more of its closest neighboring sensing elements, sensed signal levels, respectively, based on sensed light during an exposure to light. It provides, based on comparisons between said sensed signal levels and at least two different threshold levels, binarized image data of said certain sensing element and said two or more of its closest neighboring sensing elements. The imaging and processing circuit then identifies, by means of a computing element configured to operate on the provided binarized image data, said certain pixel as the local extreme point based on that the provided binarized image data of said certain sensing element differ from the provided binarized image data of said two or more of its closest neighboring sensing elements.

Abstract: Method and motion encoder for providing a measure indicative of motion of an object. The indicated motion is relative to an image sensing circuitry and in a direction that is perpendicular to an optical axis of the image sensing circuitry when the image sensing circuitry provides image frames sequentially imaging at least part of said object during the motion. The motion encoder obtains image data of a sequence of said image frames and then computes, for at least one pixel position of said sequence of image frames and based on the obtained image data, at least one duration value. Each duration value indicating a duration of consecutively occurring local extreme points in said sequence of image frames. The motion encoder then provides, based on said at least one duration value, said measure indicative of the motion.

Abstract: This document describes systems, methods, devices, and other techniques for video camera self-calibration based on video information received from the video camera. In some implementations, a computing device receives video information characterizing a video showing a scene from a field of view of a video camera; detects an object that appears in the scene of the video; identifies a visual marking that appears on the detected object; determines a particular visual marking among a plurality of pre-defined visual markings that matches the visual marking that appears on the detected object; identifies one or more object characteristics associated with the particular visual marking; evaluates one or more features of the video with respect to the one or more object characteristics; and based on a result of evaluating the one or more features of the video with respect to the one or more object characteristics, sets a parameter of the video camera.