Google Inc.

Kai Jochen Kohlhoff

Junfeng He

Shanmugasundaram Ravikumar

Nachiappan Valliappan

Michael Rubinstein

Inbar Mosseri

Badih Ghazi

Pasin Manurangsi

Kfir Aberman

David Edward Jacobs

Yael Pritch Knaan

Yossi Gandelsman

Vidhya Navalpakkam

Xiaoyi Zhang

Improved methods are provided for generating heatmaps or other summary map data from multiple users' data (e.g., probability distributions) in a manner that preserves the privacy of the users' data while also generating heatmaps that are visually similar to the 'true' heatmap. These methods include decomposing the average of the users' data (the ‘true’ heatmap) into multiple different spatial scales, injecting random noise into the data at the multiple different spatial scales, and then reconstructing the privacy-preserving heatmap based on the noisy multi-scale representations. The magnitude of the noise injected at each spatial scale is selected to ensure preservation of privacy while also resulting in heatmaps that are visually similar to the ‘true’ heatmap.

Differentially private heatmaps

Techniques for tuning an image editing operator for reducing a distractor in raw image data are presented herein. The image editing operator can access the raw image data and a mask. The mask can indicate a region of interest associated with the raw image data. The image editing operator can process the raw image data and the mask to generate processed image data. Additionally, a trained saliency model can process at least the processed image data within the region of interest to generate a saliency map that provides saliency values. Moreover, a saliency loss function can compare the saliency values provided by the saliency map for the processed image data within the region of interest to one or more target saliency values. Subsequently, the one or more parameter values of the image editing operator can be modified based at least in part on the saliency loss function.

Techniques for reducing a distraction in an image

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying a direction in which a user is looking. In one aspect, a method includes receiving an image of a sequence of images. The image can depict a face of a user. A template image for each particular facial feature point can be compared to one or more image portions of the image. The template image for the particular facial feature point can include a portion of a previous image of the sequence of images that depicted the facial feature point. Based on the comparison, a matching image portion of the image that matches the template image for the particular facial feature point is identified. A location of the matching image portion is identified in the image. A direction in which the user is looking is determined based on the identified location for each template image.

User interface control using gaze tracking

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Mountain View, CA, United States of America

Kai Jochen Kohlhoff