Patents by Inventor Srinivasa Madhava Phaneendra Angara

Srinivasa Madhava Phaneendra Angara has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 10755459
    Abstract: Techniques and systems are described herein that support improved object painting in digital images through use of perspectives and transfers in a digital medium environment. In one example, a user interacts with a two-dimensional digital image in a user interface output by a computing device to apply digital paint. The computing device fits a three-dimensional model to an object within the image, e.g., the face. The object, as fit to the three-dimensional model, is used to support output of a plurality of perspectives of a view of the object with which a user may interact to digitally paint the object. As part of this, digital paint as specified through the user inputs is applied directly by the computing device to a two-dimensional texture map of the object. This may support transfer of digital paint by a computing device between objects by transferring the digital paint using respective two-dimensional texture maps.
    Type: Grant
    Filed: October 19, 2016
    Date of Patent: August 25, 2020
    Assignee: Adobe Inc.
    Inventors: Zhili Chen, Srinivasa Madhava Phaneendra Angara, Duygu Ceylan Aksit, Byungmoon Kim, Gahye Park
  • Publication number: 20200004411
    Abstract: In various example embodiments, a system and method for providing a visual example-based user interface for adjusting images is provided. In example embodiments, a new image to be adjusted is received. A plurality of basis styles is generated by applying adjustment parameters to the new image. Each of the plurality of basis styles comprises an adjusted version of the new image with an adjustment of at least one image control. A user interface is provided that positions a version of the new image in a center portion and positions the plurality of basis styles on the user interface based on the adjustment parameters applied to the new image. A control mechanism is provided over the version of the new image whereby movement of the control mechanism to a new position on the user interface causes the version of the new image to adjust accordingly.
    Type: Application
    Filed: September 12, 2019
    Publication date: January 2, 2020
    Inventors: Sylvain Paris, Durga Ganesh Grandhi, Srinivasa Madhava Phaneendra Angara, Robert Land Gager, Sharad Baliyan
  • Patent number: 10444958
    Abstract: In various example embodiments, a system and method for providing a visual example-based user interface for adjusting images is provided. In example embodiments, a new image to be adjusted is received. A plurality of basis styles is generated by applying adjustment parameters to the new image. Each of the plurality of basis styles comprises an adjusted version of the new image with an adjustment of at least one image control. A user interface is provided that positions a version of the new image in a center portion and positions the plurality of basis styles on the user interface based on the adjustment parameters applied to the new image. A control mechanism is provided over the version of the new image whereby movement of the control mechanism to a new position on the user interface causes the version of the new image to adjust accordingly.
    Type: Grant
    Filed: September 23, 2013
    Date of Patent: October 15, 2019
    Assignee: Adobe Systems Incorporated
    Inventors: Sylvain Paris, Durga Ganesh Grandhi, Srinivasa Madhava Phaneendra Angara, Robert Land Gager, Sharad Baliyan
  • Patent number: 10380428
    Abstract: Techniques are described for analyzing a video for memorability, identifying content features of the video that are likely to be memorable, and scoring specific content features within the video for memorability. The techniques can be optionally applied to selected features in the video, thus improving the memorability of the selected features. The features may be organic features of the originally captured video or add-in features provided using an editing tool. The memorability of video features, text features, or both can be improved by analyzing the effects of applying different styles or edits (e.g., sepia tone, image sharpen, image blur, annotation, addition of object) to the content features or to the video in general. Recommendations can then be provided regarding memorability score caused by application of the image styles to the video features.
    Type: Grant
    Filed: September 26, 2017
    Date of Patent: August 13, 2019
    Assignee: Adobe Inc.
    Inventors: Sumit Shekhar, Srinivasa Madhava Phaneendra Angara, Manav Kedia, Dhruv Singal, Akhil Sathyaprakash Shetty
  • Patent number: 10198791
    Abstract: Techniques are disclosed for correcting facial sentiment of digital images. Facial data captured in a target image is analyzed to obtain facial-based sentiment. A favored sentiment is determined based at least in part on the facial-based sentiment. The favored sentiment is then applied to at least one face included in the target image that doesn't reflect the favored sentiment. Analyzing facial data may include detecting facial landmarks that are good indicators of sentiment (e.g., eyes, mouth, eyebrows, jawline, and nose). Such landmarks can be processed, with supervised machine learning, to detect the corresponding facial sentiment. A favored sentiment of the target image is thus identified, and can be applied to one or more non-compliant faces in the target image. In some embodiments, the favored sentiment can be further based on a plurality of additional sentiment indicators, including geo data, text, and/or other images associated with the target image.
    Type: Grant
    Filed: August 15, 2016
    Date of Patent: February 5, 2019
    Assignee: Adobe Inc.
    Inventors: Srinivasa Madhava Phaneendra Angara, Lance Lewis, Anmol Dhawan
  • Patent number: 10108884
    Abstract: In example embodiments, systems and methods for learning and using user preferences for image adjustments are presented. In example embodiments, a new image is received. A correction parameter based on previously stored user adjustments for similar images is determined. A user style that is an adjusted version of the new image is generated by applying the correction parameter. The user style is provided on a user interface. A user adjustment is received. Based on determining that a user sample image is within a predetermined threshold of closeness to the new image, data corresponding to the user sample image is replaced with new adjustment data for the new image in a database of user sample images used to generate the correction parameter. Based on determining that no user sample images are within the predetermined threshold of closeness, new adjustment data is appended to the database used to generate the correction parameter.
    Type: Grant
    Filed: May 13, 2016
    Date of Patent: October 23, 2018
    Assignee: ADOBE SYSTEMS INCORPORATED
    Inventors: Sylvain Paris, Durga Ganesh Grandhi, Srinivasa Madhava Phaneendra Angara, Robert Land Gager
  • Publication number: 20180108160
    Abstract: Techniques and systems are described herein that support improved object painting in digital images through use of perspectives and transfers in a digital medium environment. In one example, a user interacts with a two-dimensional digital image in a user interface output by a computing device to apply digital paint. The computing device fits a three-dimensional model to an object within the image, e.g., the face. The object, as fit to the three-dimensional model, is used to support output of a plurality of perspectives of a view of the object with which a user may interact to digitally paint the object. As part of this, digital paint as specified through the user inputs is applied directly by the computing device to a two-dimensional texture map of the object. This may support transfer of digital paint by a computing device between objects by transferring the digital paint using respective two-dimensional texture maps.
    Type: Application
    Filed: October 19, 2016
    Publication date: April 19, 2018
    Applicant: Adobe Systems Incorporated
    Inventors: Zhili Chen, Srinivasa Madhava Phaneendra Angara, Duygu Ceylan Aksit, Byungmoon Kim, Gahye Park
  • Patent number: 9928439
    Abstract: Facilitating text identification and editing in images in which in one or more embodiments, a user selection of a location in an area of text in an image is received. Given the location, a region of interest that includes text (including the location of the user selection) in the image is determined. Distortion resulting from a surface in the image on which the text is situated being at some angle other than parallel to the image capture plane is also corrected. One or more fonts and font sizes of the text in the region of interest are also detected. Various actions can be taken on the text in the region of interest (e.g., editing the text and/or identifying the text).
    Type: Grant
    Filed: January 17, 2017
    Date of Patent: March 27, 2018
    Assignee: Adobe Systems Incorporated
    Inventors: Srinivasa Madhava Phaneendra Angara, Ajay Bedi
  • Publication number: 20180047137
    Abstract: Techniques are disclosed for correcting facial sentiment of digital images. Facial data captured in a target image is analyzed to obtain facial-based sentiment. A favored sentiment is determined based at least in part on the facial-based sentiment. The favored sentiment is then applied to at least one face included in the target image that doesn't reflect the favored sentiment. Analyzing facial data may include detecting facial landmarks that are good indicators of sentiment (e.g., eyes, mouth, eyebrows, jawline, and nose). Such landmarks can be processed, with supervised machine learning, to detect the corresponding facial sentiment. A favored sentiment of the target image is thus identified, and can be applied to one or more non-compliant faces in the target image. In some embodiments, the favored sentiment can be further based on a plurality of additional sentiment indicators, including geo data, text, and/or other images associated with the target image.
    Type: Application
    Filed: August 15, 2016
    Publication date: February 15, 2018
    Applicant: Adobe Systems Incorporated
    Inventors: Srinivasa Madhava Phaneendra Angara, Lance Lewis, Anmol Dhawan
  • Publication number: 20180018523
    Abstract: Techniques are described for analyzing a video for memorability, identifying content features of the video that are likely to be memorable, and scoring specific content features within the video for memorability. The techniques can be optionally applied to selected features in the video, thus improving the memorability of the selected features. The features may be organic features of the originally captured video or add-in features provided using an editing tool. The memorability of video features, text features, or both can be improved by analyzing the effects of applying different styles or edits (e.g., sepia tone, image sharpen, image blur, annotation, addition of object) to the content features or to the video in general. Recommendations can then be provided regarding memorability score caused by application of the image styles to the video features.
    Type: Application
    Filed: September 26, 2017
    Publication date: January 18, 2018
    Applicant: Adobe Systems Incorporated
    Inventors: Sumit Shekhar, Srinivasa Madhava Phaneendra Angara, Manav Kedia, Dhruv Singal, Akhil Sathyaprakash Shetty
  • Patent number: 9805269
    Abstract: Techniques are described for analyzing a video for memorability, identifying content features of the video that are likely to be memorable, and scoring specific content features within the video for memorability. The techniques can be optionally applied to selected features in the video, thus improving the memorability of the selected features. The features may be organic features of the originally captured video or add-in features provided using an editing tool. The memorability of video features, text features, or both can be improved by analyzing the effects of applying different styles or edits (e.g., sepia tone, image sharpen, image blur, annotation, addition of object) to the content features or to the video in general. Recommendations can then be provided regarding memorability score caused by application of the image styles to the video features.
    Type: Grant
    Filed: November 20, 2015
    Date of Patent: October 31, 2017
    Assignee: ADOBE SYSTEMS INCORPORATED
    Inventors: Sumit Shekhar, Srinivasa Madhava Phaneendra Angara, Manav Kedia, Dhruv Singal, Akhil Sathyaprakash Shetty
  • Patent number: 9747526
    Abstract: In various example embodiments, a system and method for using machine learning to define user controls for image adjustment is provided. In example embodiments, a new image to be adjusted is received. A weight is applied to reference images of a reference dataset based on a comparison of content of the new image to the reference image of the reference dataset. A plurality of basis styles is generated by applying weighted averages of adjustment parameters corresponding to the weighted reference images to the new image. Each of the plurality of basis styles comprises a version of the new image with an adjustment of at least one image control based on the weighted averages of the adjustment parameters of the reference dataset. The plurality of basis styles is provided to a user interface of a display device.
    Type: Grant
    Filed: October 6, 2015
    Date of Patent: August 29, 2017
    Assignee: ADOBE SYSTEMS INCORPORATED
    Inventors: Sylvain Paris, Mohit Gupta, Srinivasa Madhava Phaneendra Angara, Durga Ganesh Grandhi
  • Publication number: 20170147906
    Abstract: Techniques are described for analyzing a video for memorability, identifying content features of the video that are likely to be memorable, and scoring specific content features within the video for memorability. The techniques can be optionally applied to selected features in the video, thus improving the memorability of the selected features. The features may be organic features of the originally captured video or add-in features provided using an editing tool. The memorability of video features, text features, or both can be improved by analyzing the effects of applying different styles or edits (e.g., sepia tone, image sharpen, image blur, annotation, addition of object) to the content features or to the video in general. Recommendations can then be provided regarding memorability score caused by application of the image styles to the video features.
    Type: Application
    Filed: November 20, 2015
    Publication date: May 25, 2017
    Applicant: ADOBE SYSTEMS INCORPORATED
    Inventors: Sumit Shekhar, Srinivasa Madhava Phaneendra Angara, Manav Kedia, Dhruv Singal, Akhil Sathyaprakash Shetty
  • Publication number: 20170124417
    Abstract: Facilitating text identification and editing in images in which in one or more embodiments, a user selection of a location in an area of text in an image is received. Given the location, a region of interest that includes text (including the location of the user selection) in the image is determined. Distortion resulting from a surface in the image on which the text is situated being at some angle other than parallel to the image capture plane is also corrected. One or more fonts and font sizes of the text in the region of interest are also detected. Various actions can be taken on the text in the region of interest (e.g., editing the text and/or identifying the text).
    Type: Application
    Filed: January 17, 2017
    Publication date: May 4, 2017
    Applicant: Adobe Systems Incorporated
    Inventors: Srinivasa Madhava Phaneendra Angara, Ajay Bedi
  • Patent number: 9576348
    Abstract: Facilitating text identification and editing in images in which in one or more embodiments, a user selection of a location in an area of text in an image is received. Given the location, a region of interest that includes text (including the location of the user selection) in the image is determined. Distortion resulting from a surface in the image on which the text is situated being at some angle other than parallel to the image capture plane is also corrected. One or more fonts and font sizes of the text in the region of interest are also detected. Various actions can be taken on the text in the region of interest (e.g., editing the text and/or identifying the text).
    Type: Grant
    Filed: November 14, 2014
    Date of Patent: February 21, 2017
    Assignee: Adobe Systems Incorporated
    Inventors: Srinivasa Madhava Phaneendra Angara, Ajay Bedi
  • Publication number: 20160253578
    Abstract: In example embodiments, systems and methods for learning and using user preferences for image adjustments are presented. In example embodiments, a new image is received. A correction parameter based on previously stored user adjustments for similar images is determined. A user style that is an adjusted version of the new image is generated by applying the correction parameter. The user style is provided on a user interface. A user adjustment is received. Based on determining that a user sample image is within a predetermined threshold of closeness to the new image, data corresponding to the user sample image is replaced with new adjustment data for the new image in a database of user sample images used to generate the correction parameter. Based on determining that no user sample images are within the predetermined threshold of closeness, new adjustment data is appended to the database used to generate the correction parameter.
    Type: Application
    Filed: May 13, 2016
    Publication date: September 1, 2016
    Inventors: Sylvain Paris, Durga Ganesh Grandhi, Srinivasa Madhava Phaneendra Angara, Robert Land Gager
  • Patent number: 9361666
    Abstract: In example embodiments, systems and methods for learning and using user preferences for image adjustments are presented. In example embodiments, a new image is received. A correction parameter based on previously stored user adjustments for similar images is determined. A user style that is an adjusted version of the new image is generated by applying the correction parameter. The user style is provided on a user interface. A user adjustment is received. Based on determining that a user sample image is within a predetermined threshold of closeness to the new image, data corresponding to the user sample image is replaced with new adjustment data for the new image in a database of user sample images used to generate the correction parameter. Based on determining that no user sample images are within the predetermined threshold of closeness, new adjustment data is appended to the database used to generate the correction parameter.
    Type: Grant
    Filed: October 7, 2013
    Date of Patent: June 7, 2016
    Assignee: ADOBE SYSTEMS INCORPORATED
    Inventors: Sylvain Paris, Durga Ganesh Grandhi, Srinivasa Madhava Phaneendra Angara, Robert Land Gager
  • Publication number: 20160140701
    Abstract: Facilitating text identification and editing in images is described herein. In one or more embodiments, a user selection of a location in an area of text in an image is received. Given the location, a region of interest that includes text (including the location of the user selection) in the image is determined. Distortion resulting from a surface in the image on which the text is situated being at some angle other than parallel to the image capture plane is also corrected. One or more fonts and font sizes of the text in the region of interest are also detected. Various actions can be taken on the text in the region of interest (e.g., editing the text and/or identifying the text).
    Type: Application
    Filed: November 14, 2014
    Publication date: May 19, 2016
    Inventors: Srinivasa Madhava Phaneendra Angara, Ajay Bedi
  • Publication number: 20160026897
    Abstract: In various example embodiments, a system and method for using machine learning to define user controls for image adjustment is provided. In example embodiments, a new image to be adjusted is received. A weight is applied to reference images of a reference dataset based on a comparison of content of the new image to the reference image of the reference dataset. A plurality of basis styles is generated by applying weighted averages of adjustment parameters corresponding to the weighted reference images to the new image. Each of the plurality of basis styles comprises a version of the new image with an adjustment of at least one image control based on the weighted averages of the adjustment parameters of the reference dataset. The plurality of basis styles is provided to a user interface of a display device.
    Type: Application
    Filed: October 6, 2015
    Publication date: January 28, 2016
    Inventors: SYLVAIN PARIS, MOHIT GUPTA, SRINIVASA MADHAVA PHANEENDRA ANGARA, DURGA GANESH GRANDHI
  • Patent number: 9195909
    Abstract: In various example embodiments, a system and method for using machine learning to define user controls for image adjustment is provided. In example embodiments, a new image to be adjusted is received. A weight is applied to reference images of a reference dataset based on a comparison of content of the new image to the reference image of the reference dataset. A plurality of basis styles is generated by applying weighted averages of adjustment parameters corresponding to the weighted reference images to the new image. Each of the plurality of basis styles comprises a version of the new image with an adjustment of at least one image control based on the weighted averages of the adjustment parameters of the reference dataset. The plurality of basis styles is provided to a user interface of a display device.
    Type: Grant
    Filed: September 23, 2013
    Date of Patent: November 24, 2015
    Assignee: ADOBE SYSTEMS INCORPORATED
    Inventors: Sylvain Paris, Mohit Gupta, Srinivasa Madhava Phaneendra Angara, Durga Ganesh Grandhi