Abstract: The present disclosure includes methods and systems for searching for digital visual media based on semantic and spatial information. In particular, one or more embodiments of the disclosed systems and methods identify digital visual media displaying targeted visual content in a targeted region based on a query term and a query area provide via a digital canvas. Specifically, the disclosed systems and methods can receive user input of a query term and a query area and provide the query term and query area to a query neural network to generate a query feature set. Moreover, the disclosed systems and methods can compare the query feature set to digital visual media feature sets. Further, based on the comparison, the disclosed systems and methods can identify digital visual media portraying targeted visual content corresponding to the query term within a targeted region corresponding to the query area.

Abstract: The technology described herein is directed to a reinforcement learning based framework for training a natural media agent to learn a rendering policy without human supervision or labeled datasets. The reinforcement learning based framework feeds the natural media agent a training dataset to implicitly learn the rendering policy by exploring a canvas and minimizing a loss function. Once trained, the natural media agent can be applied to any reference image to generate a series (or sequence) of continuous-valued primitive graphic actions, e.g., sequence of painting strokes, that when rendered by a synthetic rendering environment on a canvas, reproduce an identical or transformed version of the reference image subject to limitations of an action space and the learned rendering policy.

Abstract: Systems, apparatuses, and methods for capturing voice messages are provided. In one embodiment, a method can include receiving, by one or more processors of a mobile user device, a user input indicative of a voice message at a first time. The method can further include identifying contextual data indicative of one or more computing devices within proximity of the mobile user device. The method can include providing a set of data for storage in one or more memory devices of the mobile user device. The set of data can indicate the voice message and the contextual data indicative of the computing devices. The method can further include providing an output indicative of the voice message and the contextual data to one or more secure computing devices at a second time.

Abstract: A light-emitting system is provided which is removably attachable to headgear for personal illumination to enhance visibility of the user to others. The light-emitting system includes a housing that defines a receiving aperture and is configured to surround a portion of the headgear when the light-emitting system is removably attached to the headgear for use. The light-emitting system further includes at least one lens and a plurality of lighting elements coupled to the annular housing which are configured to selectively generate a halo or at least a partial halo of light that radiates outwardly away from the annular housing through the at least one lens to provide enhanced personal illumination.

Abstract: A light-emitting system is provided which is removably attachable to headgear for personal illumination to enhance visibility of the user to others. The light-emitting system includes a housing that defines a receiving aperture and is configured to surround a portion of the headgear when the light-emitting system is removably attached to the headgear for use. The light-emitting system further includes at least one lens and a plurality of lighting elements coupled to the annular housing which are configured to selectively generate a halo or at least a partial halo of light that radiates outwardly away from the annular housing through the at least one lens to provide enhanced personal illumination.

Abstract: Embodiments of the present invention provide an automated image tagging system that can predict a set of tags, along with relevance scores, that can be used for keyword-based image retrieval, image tag proposal, and image tag auto-completion based on user input. Initially, during training, a clustering technique is utilized to reduce cluster imbalance in the data that is input into a convolutional neural network (CNN) for training feature data. In embodiments, the clustering technique can also be utilized to compute data point similarity that can be utilized for tag propagation (to tag untagged images). During testing, a diversity based voting framework is utilized to overcome user tagging biases. In some embodiments, bigram re-weighting can down-weight a keyword that is likely to be part of a bigram based on a predicted tag set.

Abstract: A light-emitting system is provided which is removably attachable to headgear for personal illumination to enhance visibility of the user to others. The light-emitting system includes a housing that defines a receiving aperture and is configured to surround a portion of the headgear when the light-emitting system is removably attached to the headgear for use. The light-emitting system further includes at least one lens and a plurality of lighting elements coupled to the annular housing which are configured to selectively generate a halo or at least a partial halo of light that radiates outwardly away from the annular housing through the at least one lens to provide enhanced personal illumination.

Abstract: A light-emitting system is provided which is removably attachable to headgear for personal illumination to enhance visibility of the user to others. The light-emitting system includes a housing that defines a receiving aperture and is configured to surround a portion of the headgear when the light-emitting system is removably attached to the headgear for use. The light-emitting system further includes at least one lens and a plurality of lighting elements coupled to the annular housing which are configured to selectively generate a halo or at least a partial halo of light that radiates outwardly away from the annular housing through the at least one lens to provide enhanced personal illumination.

Abstract: Embodiments of the present invention provide an automated image tagging system that can predict a set of tags, along with relevance scores, that can be used for keyword-based image retrieval, image tag proposal, and image tag auto-completion based on user input. Initially, during training, a clustering technique is utilized to reduce cluster imbalance in the data that is input into a convolutional neural network (CNN) for training feature data. In embodiments, the clustering technique can also be utilized to compute data point similarity that can be utilized for tag propagation (to tag untagged images). During testing, a diversity based voting framework is utilized to overcome user tagging biases. In some embodiments, bigram re-weighting can down-weight a keyword that is likely to be part of a bigram based on a predicted tag set.

Abstract: Techniques are disclosed for image feature representation. The techniques exhibit discriminative power that can be used in any number of classification tasks, and are particularly effective with respect to fine-grained image classification tasks. In an embodiment, a given image to be classified is divided into image patches. A vector is generated for each image patch. Each image patch vector is compared to the Gaussian mixture components (each mixture component is also a vector) of a Gaussian Mixture Model (GMM). Each such comparison generates a similarity score for each image patch vector. For each Gaussian mixture component, the image patch vectors associated with a similarity score that is too low are eliminated. The selectively pooled vectors from all the Gaussian mixture components are then concatenated to form the final image feature vector, which can be provided to a classifier so the given input image can be properly categorized.

Abstract: A light-emitting system is provided which is removably attachable to headgear for personal illumination to enhance visibility of the user to others. The light-emitting system includes a housing that defines a receiving aperture and is configured to surround a portion of the headgear when the light-emitting system is removably attached to the headgear for use. The light-emitting system further includes at least one lens and a plurality of lighting elements coupled to the annular housing which are configured to selectively generate a halo or at least a partial halo of light that radiates outwardly away from the annular housing through the at least one lens to provide enhanced personal illumination.

Abstract: Techniques of directing a user to content based on a semantic interpretation of a query input by the user involves generating links to specific content in a collection of documents in response to user string query, the links being generated based on an answer suggestion lookahead index. The answer suggestion lookahead index references a mapping between a plurality of groups of semantically equivalent terms and a respective link to specific content of the collection of documents. These techniques are useful for the generalized task of natural language question answering.

Abstract: Methods and systems for recognizing people in images with increased accuracy are disclosed. In particular, the methods and systems divide images into a plurality of clusters based on common characteristics of the images. The methods and systems also determine an image cluster to which an image with an unknown person instance most corresponds. One or more embodiments determine a probability that the unknown person instance is each known person instance in the image cluster using a trained cluster classifier of the image cluster. Optionally, the methods and systems determine context weights for each combination of an unknown person instance and each known person instance using a conditional random field algorithm based on a plurality of context cues associated with the unknown person instance and the known person instances. The methods and systems calculate a contextual probability based on the cluster-based probabilities and context weights to identify the unknown person instance.

Abstract: This disclosure relates to training a classifier algorithm that can be used for automatically selecting tags to be applied to a received image. For example, a computing device can group training images together based on the training images having similar tags. The computing device trains a classifier algorithm to identify the training images as semantically similar to one another based on the training images being grouped together. The trained classifier algorithm is used to determine that an input image is semantically similar to an example tagged image. A tag is generated for the input image using tag content from the example tagged image based on determining that the input image is semantically similar to the tagged image.

Abstract: The present disclosure includes methods and systems for searching for digital visual media based on semantic and spatial information. In particular, one or more embodiments of the disclosed systems and methods identify digital visual media displaying targeted visual content in a targeted region based on a query term and a query area provide via a digital canvas. Specifically, the disclosed systems and methods can receive user input of a query term and a query area and provide the query term and query area to a query neural network to generate a query feature set. Moreover, the disclosed systems and methods can compare the query feature set to digital visual media feature sets. Further, based on the comparison, the disclosed systems and methods can identify digital visual media portraying targeted visual content corresponding to the query term within a targeted region corresponding to the query area.

Abstract: A light-emitting system is provided which is removably attachable to headgear for personal illumination to enhance visibility of the user to others. The light -emitting system includes a housing that defines a receiving aperture and is configured to surround a portion of the headgear when the light-emitting system is removably attached to the headgear for use. The light-emitting system further includes at least one lens and a plurality of lighting elements coupled to the annular housing which are configured to selectively generate a halo or at least a partial halo of light that radiates outwardly away from the annular housing through the at least one lens to provide enhanced personal illumination.

Abstract: The present disclosure is directed toward systems and methods for tracking objects in videos. For example, one or more embodiments described herein utilize various tracking methods in combination with an image search index made up of still video frames indexed from a video. One or more embodiments described herein utilize a backward and forward tracking method that is anchored by one or more key frames in order to accurately track an object through the frames of a video, even when the video is long and may include challenging conditions.

Abstract: The present disclosure includes methods and systems for searching for digital visual media based on semantic and spatial information. In particular, one or more embodiments of the disclosed systems and methods identify digital visual media displaying targeted visual content in a targeted region based on a query term and a query area provide via a digital canvas. Specifically, the disclosed systems and methods can receive user input of a query term and a query area and provide the query term and query area to a query neural network to generate a query feature set. Moreover, the disclosed systems and methods can compare the query feature set to digital visual media feature sets. Further, based on the comparison, the disclosed systems and methods can identify digital visual media portraying targeted visual content corresponding to the query term within a targeted region corresponding to the query area.

Abstract: The present disclosure is directed toward systems and methods for tracking objects in videos. For example, one or more embodiments described herein utilize various tracking methods in combination with an image search index made up of still video frames indexed from a video. One or more embodiments described herein utilize a backward and forward tracking method that is anchored by one or more key frames in order to accurately track an object through the frames of a video, even when the video is long and may include challenging conditions.

Abstract: Approaches are described for determining facial landmarks in images. An input image is provided to at least one trained neural network that determines a face region (e.g., bounding box of a face) of the input image and initial facial landmark locations corresponding to the face region. The initial facial landmark locations are provided to a 3D face mapper that maps the initial facial landmark locations to a 3D face model. A set of facial landmark locations are determined from the 3D face model. The set of facial landmark locations are provided to a landmark location adjuster that adjusts positions of the set of facial landmark locations based on the input image. The input image is presented on a user device using the adjusted set of facial landmark locations.