Abstract: This disclosure relates to methods, non-transitory computer readable media, and systems that, based on a sparse textual segment, can use machine learning models to generate document variants that are both conforming to digital content guidelines and uniquely tailored for distribution to client devices of specific audiences via specific delivery channels. To create such variants, in some embodiments, the methods, non-transitory computer readable media, and systems generate suggested modifications to a draft document that correspond to features of content-guideline-conforming documents. Additionally, or alternatively, in certain implementations, the disclosed methods, non-transitory computer readable media, and systems generate suggested modifications to a draft document that correspond to features of audience-channel-specific documents.

Abstract: This disclosure relates to methods, non-transitory computer readable media, and systems that, based on a sparse textual segment, can use machine learning models to generate document variants that are both conforming to digital content guidelines and uniquely tailored for distribution to client devices of specific audiences via specific delivery channels. To create such variants, in some embodiments, the methods, non-transitory computer readable media, and systems generate suggested modifications to a draft document that correspond to features of content-guideline-conforming documents. Additionally, or alternatively, in certain implementations, the disclosed methods, non-transitory computer readable media, and systems generate suggested modifications to a draft document that correspond to features of audience-channel-specific documents.

Abstract: The automated video enhancement system and method includes a system and method for automatically enhancing video. The automated video enhancement method uses frame-to-frame motion estimation as the basis of the video enhancement. Motion estimation includes the computation of global motion (such as camera motion) and the computation of local motion (such as pixel motion). The automated video enhancement method includes generating global alignment transforms, generating optic flow vectors, and using these global alignment transforms and optic flow vectors to enhance the video. The invention also includes video processing and enhancement techniques that use the frame-to-frame motion estimation. These techniques include a deinterlace process, a denoise process, and a warp stabilization process that performs both damped and locked stabilization.

Abstract: Techniques are disclosed to provide more efficient and improved extraction of a portion of a scene without requiring excessive user interaction. More particularly, the extraction may be achieved by using iterated graph cuts. In an implementation, a method includes segmenting an image into a foreground portion and a background portion (e.g., where an object or desired portion to be extracted is present in the foreground portion). The method determines the properties corresponding to the foreground and background portions of the image. Distributions may be utilized to model the foreground and background properties. The properties may be color in one implementation and the distributions may be a Gaussian Mixture Model in another implementation. The foreground and background properties are updated based on the portions. And, the foreground and background portions are updated based on the updated foreground and background properties.

Abstract: The present invention is embodied in a system and method for extracting structure from multiple images of a scene by representing the scene as a group of image layers, including reflection and transparency layers. In general, the present invention performs layer extraction from multiple images containing reflections and transparencies. The present invention includes an optimal approach for recovering layer images and their associated motions from an arbitrary number of composite images. The present invention includes image formation equations, the constrained least squares technique used to recover the component images, a novel method to estimate upper and lower bounds on the solution using min- and max-composites, and a motion refinement method.

Abstract: A system and method for providing a peer-to-peer photo-sharing environment. The system includes: manual and automatic photo annotation at the client; periodic client-server synchronization; an index of client photos on a central server or a photo database that is resident on the central server, which is updated by the client-server synchronization function; end-user search functionality to search the centralized index or photo database; and transmission of the relevant photos to the client via an on-line image cache. In one embodiment, one client's new photos are automatically displayed on another client's computer (e.g., via screen saver or another mechanism).

Abstract: An automatic video enhancement system and method for automatically enhancing video. The automated video enhancement method uses frame-to-frame motion estimation as the basis of the video enhancement. Motion estimation includes the computation of global motion (such as camera motion) and the computation of local motion (such as pixel motion). The automated video enhancement method includes generating global alignment transforms, generating optic flow vectors, and using these global alignment transforms and optic flow vectors to enhance the video. The invention also includes video processing and enhancement techniques that use the frame-to-frame motion estimation. These techniques include a deinterlace process, a denoise process, and a warp stabilization process that performs both damped and locked stabilization.

Abstract: An automatic video enhancement system and method for automatically enhancing video. The automated video enhancement method uses frame-to-frame motion estimation as the basis of the video enhancement. Motion estimation includes the computation of global motion (such as camera motion) and the computation of local motion (such as pixel motion). The automated video enhancement method includes generating global alignment transforms, generating optic flow vectors, and using these global alignment transforms and optic flow vectors to enhance the video. The invention also includes video processing and enhancement techniques that use the frame-to-frame motion estimation. These techniques include a deinterlace process, a denoise process, and a warp stabilization process that performs both damped and locked stabilization.

Abstract: An automatic video enhancement system and method for automatically enhancing video. The automated video enhancement method uses frame-to-frame motion estimation as the basis of the video enhancement. Motion estimation includes the computation of global motion (such as camera motion) and the computation of local motion (such as pixel motion). The automated video enhancement method includes generating global alignment transforms, generating optic flow vectors, and using these global alignment transforms and optic flow vectors to enhance the video. The invention also includes video processing and enhancement techniques that use the frame-to-frame motion estimation. These techniques include a deinterlace process, a denoise process, and a warp stabilization process that performs both damped and locked stabilization.

Abstract: The automated video enhancement system and method includes a system and method for automatically enhancing video. The automated video enhancement method uses frame-to-frame motion estimation as the basis of the video enhancement. Motion estimation includes the computation of global motion (such as camera motion) and the computation of local motion (such as pixel motion). The automated video enhancement method includes generating global alignment transforms, generating optic flow vectors, and using these global alignment transforms and optic flow vectors to enhance the video. The invention also includes video processing and enhancement techniques that use the frame-to-frame motion estimation. These techniques include a deinterlace process, a denoise process, and a warp stabilization process that performs both damped and locked stabilization.

Abstract: The present invention is embodied in a system and method for extracting structure from multiple images of a scene by representing the scene as a group of image layers, including reflection and transparency layers. In general, the present invention performs layer extraction from multiple images containing reflections and transparencies. The present invention includes an optimal approach for recovering layer images and their associated motions from an arbitrary number of composite images. The present invention includes image formation equations, the constrained least squares technique used to recover the component images, a novel method to estimate upper and lower bounds on the solution using min- and max-composites, and a motion refinement method.

Abstract: The present invention includes an automatic video enhancement system and method for automatically enhancing video. The automated video enhancement method uses frame-to-frame motion estimation as the basis of the video enhancement. Motion estimation includes the computation of global motion (such as camera motion) and the computation of local motion (such as pixel motion). The automated video enhancement method includes generating global alignment transforms, generating optic flow vectors, and using these global alignment transforms and optic flow vectors to enhance the video. The invention also includes video processing and enhancement techniques that use the frame-to-frame motion estimation. These techniques include a deinterlace process, a denoise process, and a warp stabilization process that performs both damped and locked stabilization.

Abstract: An automatic video enhancement system and method for automatically enhancing video. The automated video enhancement method uses frame-to-frame motion estimation as the basis of the video enhancement. Motion estimation includes the computation of global motion (such as camera motion) and the computation of local motion (such as pixel motion). The automated video enhancement method includes generating global alignment transforms, generating optic flow vectors, and using these global alignment transforms and optic flow vectors to enhance the video. The invention also includes video processing and enhancement techniques that use the frame-to-frame motion estimation. These techniques include a deinterlace process, a denoise process, and a warp stabilization process that performs both damped and locked stabilization.

Abstract: An automatic video enhancement system and method for automatically enhancing video. The automated video enhancement method uses frame-to-frame motion estimation as the basis of the video enhancement. Motion estimation includes the computation of global motion (such as camera motion) and the computation of local motion (such as pixel motion). The automated video enhancement method includes generating global alignment transforms, generating optic flow vectors, and using these global alignment transforms and optic flow vectors to enhance the video. The invention also includes video processing and enhancement techniques that use the frame-to-frame motion estimation. These techniques include a deinterlace process, a denoise process, and a warp stabilization process that performs both damped and locked stabilization.

Abstract: An automatic video enhancement system and method for automatically enhancing video. The automated video enhancement method uses frame-to-frame motion estimation as the basis of the video enhancement. Motion estimation includes the computation of global motion (such as camera motion) and the computation of local motion (such as pixel motion). The automated video enhancement method includes generating global alignment transforms, generating optic flow vectors, and using these global alignment transforms and optic flow vectors to enhance the video. The invention also includes video processing and enhancement techniques that use the frame-to-frame motion estimation. These techniques include a deinterlace process, a denoise process, and a warp stabilization process that performs both damped and locked stabilization.

Abstract: A system and method for providing a peer-to-peer photo-sharing environment. The system includes: manual and automatic photo annotation at the client; periodic client-server synchronization; an index of client photos on a central server or a photo database that is resident on the central server, which is updated by the client-server synchronization function; end-user search functionality to search the centralized index or photo database; and transmission of the relevant photos to the client via an on-line image cache. In one embodiment, one client's new photos are automatically displayed on another client's computer (e.g., via screen saver or another mechanism).

Abstract: A system and method for providing a peer-to-peer photo-sharing environment. The system includes: manual and automatic photo annotation at the client; periodic client-server synchronization; an index of client photos on a central server or a photo database that is resident on the central server, which is updated by the client-server synchronization function; end-user search functionality to search the centralized index or photo database; and transmission of the relevant photos to the client via an on-line image cache. In one embodiment, one client's new photos are automatically displayed on another client's computer (e.g., via screen saver or another mechanism).

Abstract: The present invention is embodied in a system and method for extracting structure from multiple images of a scene by representing the scene as a group of image layers, including reflection and transparency layers. In general, the present invention performs layer extraction from multiple images containing reflections and transparencies. The present invention includes an optimal approach for recovering layer images and their associated motions from an arbitrary number of composite images. The present invention includes image formation equations, the constrained least squares technique used to recover the component images, a novel method to estimate upper and lower bounds on the solution using min- and max-composites, and a motion refinement method.

Abstract: The present invention is embodied in a system and method for extracting structure from multiple images of a scene by representing the scene as a group of image layers, including reflection and transparency layers. In general, the present invention performs layer extraction from multiple images containing reflections and transparencies. The present invention includes an optimal approach for recovering layer images and their associated motions from an arbitrary number of composite images. The present invention includes image formation equations, the constrained least squares technique used to recover the component images, a novel method to estimate upper and lower bounds on the solution using min- and max-composites, and a motion refinement method.

Abstract: The present invention is embodied in a system and method for extracting structure from multiple images of a scene by representing the scene as a group of image layers, including reflection and transparency layers. In general, the present invention performs layer extraction from multiple images containing reflections and transparencies. The present invention includes an optimal approach for recovering layer images and their associated motions from an arbitrary number of composite images. The present invention includes image formation equations, the constrained least squares technique used to recover the component images, a novel method to estimate upper and lower bounds on the solution using min- and max-composites, and a motion refinement method.