Abstract: Methods and systems for automated faux-manual image-marking of a digital image are disclosed, including a method comprising obtaining results of an automated analysis of one or more digital image indicative of determinations of structure abnormalities of one or more portions of a structure depicted in the one or more digital image; applying automatically, on the one or more digital image, with one or more computer processors, standardized markings indicative of the location in the image of the structure abnormalities of the structure depicted in the image; and generating, automatically with the one or more computer processors, one or more faux-manual markings by modifying one or more of the standardized markings, utilizing one or more image-manipulation algorithm, wherein the faux-manual markings mimic an appearance of manual markings on the structure in the real world.

Abstract: Methods and systems for automated faux-manual image-marking of a digital image are disclosed, including a method comprising obtaining results of an automated analysis of one or more digital image indicative of determinations of structure abnormalities of one or more portions of a structure depicted in the one or more digital image; applying automatically, on the one or more digital image, with one or more computer processors, standardized markings indicative of the location in the image of the structure abnormalities of the structure depicted in the image; and generating, automatically with the one or more computer processors, one or more faux-manual markings by modifying one or more of the standardized markings, utilizing one or more image-manipulation algorithm, wherein the faux-manual markings mimic an appearance of manual markings on the structure in the real world.

Abstract: A server includes an input node to receive video streams forming a panoramic video. A module forms a suggested field of view in the panoramic video. The suggested field of view is based upon a viewing parameter, such as a client device motion parameter or a motion prediction parameter. An output node sends the suggested field of view to a client device.

Abstract: A server includes an input node to receive video streams forming a panoramic video. A module forms a suggested field of view in the panoramic video. An output node sends the suggested field of view to a client device.

Abstract: A server includes an input node to receive video streams forming a panoramic video. A module forms a suggested field of view in the panoramic video. The suggested field of view is based upon a viewing parameter, such as a client device motion parameter or a motion prediction parameter. An output node sends the suggested field of view to a client device.

Abstract: A server includes an input node to receive video streams forming a panoramic video. The server also receives audio tracks corresponding to the video streams. A module forms an audio track based upon a combination of at least two of the audio tracks and directional viewing data. The audio track may be a stereo, mixed or surround sound audio track with volume modulation based upon the directional viewing data. An output node sends the audio track to a client device.

Abstract: A server includes an input node to receive video streams forming a panoramic video. A module forms a suggested field of view in the panoramic video. An output node sends the suggested field of view to a client device.