Abstract: A generative interactive video computer-implemented method and system applies trained computer-implemented neural networks to generate a sequence of images, which may comprise a video, and which contains identified objects, and then delivers the sequence of images to a user. The sequence of images may be further generated in accordance with an inference of a preference from user behavioral information. The identified objects may be provided to the system in the form of natural language and/or images. The system then generates and delivers to users natural language-based responses to user requests for information with respect to the identified objects, including attributes that are associated with the identified objects. Users may direct the system to generate video-based virtual environments that include representations of the identified objects.

Abstract: A contextual-based method and system for identifying and revealing objects from video directs a focus of attention to images or sequences of images responsive to a command, interrogative, or inferred preference of a user. A probability is assigned to an object that is inferred to be represented in the images or sequence of images. The probability is generated by application of a computer-implemented neural network. The probability is then updated based upon a context within which the representation of the object is inferred to be situated. The context may be inferred from one or more inferences related to one or more archetypical objects that are associated with the context. In accordance with the updated probability, a communication may be delivered that references attributes of the object and/or the user may direct a command to the representation of the object.

Abstract: A method and system for incentivized neural network training and assurance processes provides incentives to object miners to identify objects in video streams for the purposes of enhancing the training of computer-implemented neural networks on the identified objects and/or augmenting the results of automatic object identification by trained neural networks. An object mining user interface and process is provided to object miners that provides incentives for identifying objects in video streams and technical capabilities for designating identified objects within multiple multi-dimensional regions of pixels. Incentives may be token-based and in accordance with end user interactions within a visual user interface with representations of the miner-identified objects within a video stream.

Abstract: A method, system, and device for audio-based identification interfaces for selecting objects from video generates and stores frequency-based audio identifiers associated with segments of an audio stream that is integrated with a video stream. The generation of the frequency-based audio identifiers may be performed by a hashing function applied to audio frequencies within audio segments. The video stream comprises identified objects that may be identified by application of a trained neural network. An audio segment is received from a user and a corresponding frequency-based audio identifier is generated and matched against stored frequency-based audio identifiers. The matching determines an audio segment and a temporally corresponding identified object, which is then embodied within an interactive user interface.

Abstract: A method and system for virtual environment-based interfaces applied to selected objects from video directs a system's focus of attention to an image within a first video stream and identifies an object in the image by applying a trained neural network. In response to a communication from a user comprising language and/or images describing a virtual environment, a second trained neural network is applied to generate a second video stream that embodies the identified object within a virtual environment that is in accordance with the user-described virtual environment. The second video stream is then delivered to the user. The system's focus of attention and/or generation of the virtual environment may be informed by user preferences that are inferred from user behaviors.

Abstract: A method and system for incentivized neural network training and assurance processes provides incentives to object miners to identify objects in video streams for the purposes of enhancing the training of computer-implemented neural networks on the identified objects and/or augmenting the results of automatic object identification by trained neural networks. An object mining user interface and process is provided to object miners that provides incentives for identifying objects in video streams and technical capabilities for designating identified objects within multiple multi-dimensional regions of pixels. Incentives may be token-based and in accordance with end user interactions within a visual user interface with representations of the miner-identified objects within a video stream.

Abstract: A computer-implemented visual interface for identifying and revealing objects from video-based media provides visual cues to enable users to interact with video-based media. Objects in videos are inferred and identified based upon automatic interpretations of the video and/or audio that is associated with the video. The automatic interpretations may be performed by a computer-implemented neural network. The computer-implemented visual interface is integrated with the video to enable users to interact with the identified objects. User interactions with the visual interface may be through either touch or non-touch means. Information is delivered to users that is based upon the identified objects, including in augmented or virtual reality-based form, responsive to user interactions with the computer-implemented visual interface.

Abstract: A contextual-based method and system for identifying and revealing objects from video directs a focus of attention to images or sequences of images responsive to a command, interrogative, or inferred preference of a user. A probability is assigned to an object that is inferred to be represented in the images or sequence of images. The probability is generated by application of a computer-implemented neural network. The probability is then updated based upon a context within which the representation of the object is inferred to be situated. The context may be inferred from one or more inferences related to one or more archetypical objects that are associated with the context. In accordance with the updated probability, a communication may be delivered that references attributes of the object and/or the user may direct a command to the representation of the object.

Abstract: A method, system, and apparatus for identifying and revealing objects from video identifies or infers objects from images or sequences of images upon a command, interrogative, or inferred interest of a user. The system is trained to identify or infer the objects using neural network or statistical learning-based models. The system may respond to the user in accordance with an expected user latency in requesting the system to reveal a specific object to the user. Semantic techniques may be applied to enable the system to interpret contextual or object attribute information that is provided by the users' communications to the system. The system may be applied in product promotional processes that are with respect to video that is associated with television, movies, and other video content.

Abstract: A computer-implemented visual interface for identifying and revealing objects from video-based media provides visual cues to enable users to interact with video-based media. Objects in videos are inferred and identified based upon automatic interpretations of the video and/or audio that is associated with the video. The automatic interpretations may be performed by a computer-implemented neural network. The computer-implemented visual interface is integrated with the video to enable users to interact with the identified objects. User interactions with the visual interface may be through either touch or non-touch means. Information is delivered to users that is based upon the identified objects, including in augmented or virtual reality-based form, responsive to user interactions with the computer-implemented visual interface.

Abstract: A method, system, and apparatus for identifying and revealing objects from video identifies or infers objects from images or sequences of images upon a command, interrogative, or inferred interest of a user. The system is trained to identify or infer the objects using neural network or statistical learning-based models. The system may respond to the user in accordance with an expected user latency in requesting the system to reveal a specific object to the user. Semantic techniques may be applied to enable the system to interpret contextual or object attribute information that is provided by the users' communications to the system. The system may be applied in product promotional processes that are with respect to video that is associated with television, movies, and other video content.