Abstract: To prevent the transmission of excluded data, a short time-delay between capture and transmission of a video signal is exploited to process the buffered frames to recognize disallowed objects and control the video camera to prevent transmission of any frame including the disallowed object in the video signal. The time-delay can be implemented in real or near real time with, for example, a delay line or memory chip that serve to buffer the sequence of image frames.

Abstract: To prevent the capture and transmission of excluded data, a short time-delay between an object recognition sensor and the video camera is exploited to recognize disallowed objects and control the video camera to interrupt and stop images from being transferred into the memory chip where the video signal is formed. The time-delay can also be used to enforce an alignment condition of the video camera to an allowed object. The time-delay can be implemented in real or near real time with a delay line or temporary memory chip positioned between the video camera's ROIC and memory chip. The time-delay prevents the excluded data from entering the video signal and reaching circuitry or being processed downstream of the memory chip.

Abstract: To prevent the transmission of excluded data, a short time-delay between capture and transmission of a video signal is exploited to process the buffered frames to recognize disallowed objects and control the video camera to prevent transmission of any frame including the disallowed object in the video signal. The time-delay can be implemented in real or near real time with, for example, a delay line or memory chip that serve to buffer the sequence of image frames.

Abstract: A hybrid computer/human method for generating, validating and using a ground truth map (GTM) provides for enforcement of data capture and transmission compliance of real and near real time video. Computer-implemented processes are used to identify and classify as allowed or disallowed objects in a local scene based on attributes of a video session. A human interface is available to validate either the object identification or classification. The GTM is then used, preferably in conjunction with motion sense, to enforce data capture and transmission compliance of real and near real time video within the local scene.

Abstract: To prevent the capture and transmission of excluded data, the current pose and motion of a video camera are used to predict a pose and predicted FOV for the video camera over one or more future frames. The predicted pose and predicted FOV are used to generate cues to enforce an alignment condition to an allowed object or to prevent capture of a disallowed object. If the cues fail, an interrupt is generated to prevent capture of disallowed objects in the video signal and perhaps to deactivate the video camera. The predicted FOV prevents excluded data from entering the video signal and reaching circuitry or being processed downstream of the video camera. This can be implemented in real or near real time.

Abstract: To prevent the capture and transmission of excluded data, a short time-delay between an object recognition sensor and the video camera is exploited to recognize disallowed objects and control the video camera to interrupt and stop images from being transferred into the memory chip where the video signal is formed. The time-delay can also be used to enforce an alignment condition of the video camera to an allowed object. The time-delay can be implemented in real or near real time with a delay line or temporary memory chip positioned between the video camera’s ROIC and memory chip. The time-delay prevents the excluded data from entering the video signal and reaching circuitry or being processed downstream of the memory chip.

Abstract: To prevent the capture and transmission of excluded data, the current pose and motion of a video camera are used to predict a pose and predicted FOV for the video camera over one or more future frames. The predicted pose and predicted FOV are used to generate cues to enforce an alignment condition to an allowed object or to prevent capture of a disallowed object. If the cues fail, an interrupt is generated to prevent capture of disallowed objects in the video signal and perhaps to deactivate the video camera. The predicted FOV prevents excluded data from entering the video signal and reaching circuitry or being processed downstream of the video camera. This can be implemented in real or near real time.