Abstract: Systems and methods for displaying augmented reality content relative to an identified object are disclosed. The systems and methods can include a set of operations. An operation can include providing a first image. An operation can include determining interest points in the first image. An operation can include identifying an object in the first image. An operation can include identifying augmented reality content associated with the object. An operation can include determining a first transformation for displaying the augmented reality content in the first image relative to the identified object. An operation can include providing the interest points and the first transformation. An operation can include determining a second transformation for displaying the augmented reality content in a second image relative to the identified object using, at least in part, the first transformation and the interest points. An operation can include displaying, by a user device, the augmented reality content.

Abstract: Systems and methods for displaying augmented reality content relative to an identified object are disclosed. The systems and methods can include a set of operations. An operation can include providing a first image. An operation can include determining interest points in the first image. An operation can include identifying an object in the first image. An operation can include identifying augmented reality content associated with the object. An operation can include determining a first transformation for displaying the augmented reality content in the first image relative to the identified object. An operation can include providing the interest points and the first transformation. An operation can include determining a second transformation for displaying the augmented reality content in a second image relative to the identified object using, at least in part, the first transformation and the interest points. An operation can include displaying, by a user device, the augmented reality content.

Abstract: Systems and methods for displaying augmented reality content relative to an identified object are disclosed. The systems and methods can include a set of operations. An operation can include providing a first image. An operation can include determining interest points in the first image. An operation can include identifying an object in the first image. An operation can include identifying augmented reality content associated with the object. An operation can include determining a first transformation for displaying the augmented reality content in the first image relative to the identified object. An operation can include providing the interest points and the first transformation. An operation can include determining a second transformation for displaying the augmented reality content in a second image relative to the identified object using, at least in part, the first transformation and the interest points. An operation can include displaying, by a user device, the augmented reality content.

Abstract: The present disclosure provides systems and methods for providing augmented reality experiences. Consistent with disclosed embodiments, one or more machine-learning models can be trained to selectively process image data. A pre-processor can be configured to receive image data provided by a user device and trained to automatically determine whether to select and apply a preprocessing technique to the image data. A classifier can be trained to identify whether the image data received from the pre-processor includes a match to one of a plurality of triggers. A selection engine can be trained to select, based on a matched trigger and in response to the identification of the match, a processing engine. The processing engine can be configured to generate an output using the image data, and store the output or provide the output to the user device or a client system.

Abstract: Methods and systems are described herein that allow a user to capture a single image snapshot from video, print, or the world around him or her, and obtain additional information relating to the media itself or items of interest displayed in the snapshot. A fingerprint of the snapshot is used as a query and transmitted to the server. Image Feature-Based Recognition, as described herein, uses a feature index to identify a smaller set of candidate matches from a larger database of images based on the fingerprint. Novel methods and systems using a distance metric and a radical hash table design exploit probabilistic effects and allow distinct image features to be preferred over redundant ones, allowing only the more distinctive data points to remain resident within the index, yielding a lean index that can be quickly used in the identification process.

Abstract: The present disclosure provides systems and methods for providing augmented reality experiences. Consistent with disclosed embodiments, one or more machine-learning models can be trained to selectively process image data. A pre-processor can be configured to receive image data provided by a user device and trained to automatically determine whether to select and apply a preprocessing technique to the image data. A classifier can be trained to identify whether the image data received from the pre-processor includes a match to one of a plurality of triggers. A selection engine can be trained to select, based on a matched trigger and in response to the identification of the match, a processing engine. The processing engine can be configured to generate an output using the image data, and store the output or provide the output to the user device or a client system.

Abstract: The present disclosure provides systems and methods for providing augmented reality experiences. Consistent with disclosed embodiments, one or more machine-learning models can be trained to selectively process image data. A pre-processor can be configured to receive image data provided by a user device and trained to automatically determine whether to select and apply a preprocessing technique to the image data. A classifier can be trained to identify whether the image data received from the pre-processor includes a match to one of a plurality of triggers. A selection engine can be trained to select, based on a matched trigger and in response to the identification of the match, a processing engine. The processing engine can be configured to generate an output using the image data, and store the output or provide the output to the user device or a client system.

Abstract: Methods and systems are described herein that allow a user to capture a single image snapshot from video, print, or the world around him or her, and obtain additional information relating to the media itself or items of interest displayed in the snapshot. A fingerprint of the snapshot is used as a query and transmitted to the server. Image Feature-Based Recognition, as described herein, uses a feature index to identify a smaller set of candidate matches from a larger database of images based on the fingerprint. Novel methods and systems using a distance metric and a radical hash table design exploit probabilistic effects and allow distinct image features to be preferred over redundant ones, allowing only the more distinctive data points to remain resident within the index, yielding a lean index that can be quickly used in the identification process.

Abstract: Methods and systems are described herein that allow a user to capture a single image snapshot from video, print, or the world around him or her, and obtain additional information relating to the media itself or items of interest displayed in the snapshot. A fingerprint of the snapshot is used as a query and transmitted to the server. Image Feature-Based Recognition, as described herein, uses a feature index to identify a smaller set of candidate matches from a larger database of images based on the fingerprint. Novel methods and systems using a distance metric and a radical hash table design exploit probabilistic effects and allow distinct image features to be preferred over redundant ones, allowing only the more distinctive data points to remain resident within the index, yielding a lean index that can be quickly used in the identification process.

Abstract: Methods and systems are described herein that allow a user to capture a single image snapshot from video, print, or the world around him or her, and obtain additional information relating to the media itself or items of interest displayed in the snapshot. A fingerprint of the snapshot is used as a query and transmitted to the server. Image Feature-Based Recognition, as described herein, uses a feature index to identify a smaller set of candidate matches from a larger database of images based on the fingerprint. Novel methods and systems using a distance metric and a radical hash table design exploit probabilistic effects and allow distinct image features to be preferred over redundant ones, allowing only the more distinctive data points to remain resident within the index, yielding a lean index that can be quickly used in the identification process.

Abstract: Methods and systems are described herein that allow a user to capture a single image snapshot from video, print, or the world around him or her, and obtain additional information relating to the media itself or items of interest displayed in the snapshot. A fingerprint of the snapshot is used as a query and transmitted to the server. Image Feature-Based Recognition, as described herein, uses a feature index to identify a smaller set of candidate matches from a larger database of images based on the fingerprint. Novel methods and systems using a distance metric and a radical hash table design exploit probabilistic effects and allow distinct image features to be preferred over redundant ones, allowing only the more distinctive data points to remain resident within the index, yielding a lean index that can be quickly used in the identification process.

Abstract: Methods and systems are described herein that allow a user to capture a single image snapshot from video, print, or the world around him or her, and obtain additional information relating to the media itself or items of interest displayed in the snapshot. A fingerprint of the snapshot is used as a query and transmitted to the server. Image Feature-Based Recognition, as described herein, uses a feature index to identify a smaller set of candidate matches from a larger database of images based on the fingerprint. Novel methods and systems using a distance metric and a radical hash table design exploit probabilistic effects and allow distinct image features to be preferred over redundant ones, allowing only the more distinctive data points to remain resident within the index, yielding a lean index that can be quickly used in the identification process.