Patents by Inventor AKSHAY MALHOTRA
AKSHAY MALHOTRA 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).
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Publication number: 20240048669Abstract: Techniques for managing coverage constraints are provided for determining an improved camera coverage plan including a number, a placement, and a pose of cameras that are arranged to track puts and takes of items by subjects in a three-dimensional real space. The method includes receiving an initial camera coverage plan including a three-dimensional map of a real space, an initial number and initial pose of a plurality of cameras and a camera model including characteristics of the cameras. The method can iteratively apply a machine learning process to an objective function of number and poses of cameras, and subject to a set of constraints, obtain an improved camera coverage plan. The improved camera coverage plan is provided to an installer to arrange cameras to track puts and takes of items by subjects in the three-dimensional real space.Type: ApplicationFiled: October 12, 2023Publication date: February 8, 2024Applicant: STANDARD COGNITION, CORP.Inventors: Nagasrikanth KALLAKURI, Akshay MALHOTRA, Luis Yoichi MORALES SAIKI, Tushar DADLANI, Dhananjay SINGH
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Patent number: 11818508Abstract: Systems and techniques are provided for determining an improved camera coverage plan including a number, a placement, and a pose of cameras that are arranged to track puts and takes of items by subjects in a three-dimensional real space. The method includes receiving an initial camera coverage plan including a three-dimensional map of a real space, an initial number and initial pose of a plurality of cameras and a camera model including characteristics of the cameras. The method can iteratively apply a machine learning process to an objective function of number and poses of cameras, and subject to a set of constraints, obtain an improved camera coverage plan. The improved camera coverage plan is provided to an installer to arrange cameras to track puts and takes of items by subjects in the three-dimensional real space.Type: GrantFiled: February 25, 2022Date of Patent: November 14, 2023Assignee: STANDARD COGNITION, CORP.Inventors: Nagasrikanth Kallakuri, Akshay Malhotra, Luis Yoichi Morales Saiki, Tushar Dadlani, Dhananjay Singh
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Patent number: 11783486Abstract: Generating images and videos depicting a human subject wearing textually defined attire is described. An image generation system receives a two-dimensional reference image depicting a person and a textual description describing target clothing in which the person is to be depicted as wearing. To maintain a personal identity of the person, the image generation system implements a generative model, trained using both discriminator loss and perceptual quality loss, which is configured to generate images from text. In some implementations, the image generation system is configured to train the generative model to output visually realistic images depicting the human subject in the target clothing. The image generation system is further configured to apply the trained generative model to process individual frames of a reference video depicting a person and output frames depicting the person wearing textually described target clothing.Type: GrantFiled: December 16, 2021Date of Patent: October 10, 2023Assignee: Adobe Inc.Inventors: Viswanathan Swaminathan, Gang Wu, Akshay Malhotra
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Patent number: 11601134Abstract: A system and method for generating and using fixed-point operations for neural networks includes converting floating-point weighting factors into fixed-point weighting factors using a scaling factor. The scaling factor is defined to minimize a cost function and the scaling factor is derived from a set of multiples of a predetermined base. The set of possible scaling function is defined to reduce the computational effort for evaluating the cost function for each of a number of possible scaling factors. The system and method may be implemented in one or more controllers that are programmed to execute the logic.Type: GrantFiled: January 10, 2020Date of Patent: March 7, 2023Assignee: Robert Bosch GmbHInventors: Akshay Malhotra, Thomas Rocznik, Christian Peters
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Patent number: 11575947Abstract: Residual vectors are compressed in a lossless compression scheme suitable for cloud DVR video content applications. Thus, a cloud DVR service provider can take many copies of the same file stored in the cloud and save storage space by compressing those copies while still maintaining their status as distinct copies, one per user. Vector quantization is used for compressing already-compressed video streams (e.g., MPEG streams). As vector quantization is a lossy compression scheme, the residual vector has to be stored to regenerate the original video stream at the decoding (playback) node. Entropy coding schemes like Arithmetic or Huffman coding can be used to compress the residual vectors. Additional strategies can be implemented to further optimize this residual compression. In some embodiments, the techniques operate to provide a 25-50% improvement in compression. Storage space is thus more efficiently used and video transmission may be faster in some cases.Type: GrantFiled: June 4, 2021Date of Patent: February 7, 2023Assignee: Adobe Inc.Inventors: Viswanathan Swaminathan, Saayan Mitra, Akshay Malhotra
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Publication number: 20220279144Abstract: Systems and techniques are provided for determining an improved camera coverage plan including a number, a placement, and a pose of cameras that are arranged to track puts and takes of items by subjects in a three-dimensional real space. The method includes receiving an initial camera coverage plan including a three-dimensional map of a real space, an initial number and initial pose of a plurality of cameras and a camera model including characteristics of the cameras. The method can iteratively apply a machine learning process to an objective function of number and poses of cameras, and subject to a set of constraints, obtain an improved camera coverage plan. The improved camera coverage plan is provided to an installer to arrange cameras to track puts and takes of items by subjects in the three-dimensional real space.Type: ApplicationFiled: February 25, 2022Publication date: September 1, 2022Applicant: STANDARD COGNITION, CORP.Inventors: Nagasrikanth KALLAKURI, Akshay MALHOTRA, Luis Yoichi MORALES SAIKI, Tushar DADLANI, Dhananjay SINGH
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Patent number: 11303853Abstract: Systems and techniques are provided for determining an improved camera coverage plan including a number, a placement, and a pose of cameras that are arranged to track puts and takes of items by subjects in a three-dimensional real space. The method includes receiving an initial camera coverage plan including a three-dimensional map of a real space, an initial number and initial pose of a plurality of cameras and a camera model including characteristics of the cameras. The method can iteratively apply a machine learning process to an objective function of number and poses of cameras, and subject to a set of constraints, obtain an improved camera coverage plan. The improved camera coverage plan is provided to an installer to arrange cameras to track puts and takes of items by subjects in the three-dimensional real space.Type: GrantFiled: June 25, 2021Date of Patent: April 12, 2022Assignee: STANDARD COGNITION, CORP.Inventors: Nagasrikanth Kallakuri, Akshay Malhotra, Luis Yoichi Morales Saiki, Tushar Dadlani, Dhananjay Singh
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Publication number: 20220108509Abstract: Generating images and videos depicting a human subject wearing textually defined attire is described. An image generation system receives a two-dimensional reference image depicting a person and a textual description describing target clothing in which the person is to be depicted as wearing. To maintain a personal identity of the person, the image generation system implements a generative model, trained using both discriminator loss and perceptual quality loss, which is configured to generate images from text. In some implementations, the image generation system is configured to train the generative model to output visually realistic images depicting the human subject in the target clothing. The image generation system is further configured to apply the trained generative model to process individual frames of a reference video depicting a person and output frames depicting the person wearing textually described target clothing.Type: ApplicationFiled: December 16, 2021Publication date: April 7, 2022Applicant: Adobe Inc.Inventors: Viswanathan Swaminathan, Gang Wu, Akshay Malhotra
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Publication number: 20210409648Abstract: Systems and techniques are provided for determining an improved camera coverage plan including a number, a placement, and a pose of cameras that are arranged to track puts and takes of items by subjects in a three-dimensional real space. The method includes receiving an initial camera coverage plan including a three-dimensional map of a real space, an initial number and initial pose of a plurality of cameras and a camera model including characteristics of the cameras. The method can iteratively apply a machine learning process to an objective function of number and poses of cameras, and subject to a set of constraints, obtain an improved camera coverage plan. The improved camera coverage plan is provided to an installer to arrange cameras to track puts and takes of items by subjects in the three-dimensional real space.Type: ApplicationFiled: June 25, 2021Publication date: December 30, 2021Applicant: STANDARD COGNITION, CORP.Inventors: Nagasrikanth KALLAKURI, Akshay MALHOTRA, Luis Yoichi MORALES SAIKI, Tushar DADLANI, Dhananjay SINGH
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Patent number: 11210831Abstract: Generating images and videos depicting a human subject wearing textually defined attire is described. An image generation system receives a two-dimensional reference image depicting a person and a textual description describing target clothing in which the person is to be depicted as wearing. To maintain a personal identity of the person, the image generation system implements a generative model, trained using both discriminator loss and perceptual quality loss, which is configured to generate images from text. In some implementations, the image generation system is configured to train the generative model to output visually realistic images depicting the human subject in the target clothing. The image generation system is further configured to apply the trained generative model to process individual frames of a reference video depicting a person and output frames depicting the person wearing textually described target clothing.Type: GrantFiled: February 28, 2020Date of Patent: December 28, 2021Assignee: Adobe Inc.Inventors: Viswanathan Swaminathan, Gang Wu, Akshay Malhotra
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Publication number: 20210297708Abstract: Residual vectors are compressed in a lossless compression scheme suitable for cloud DVR video content applications. Thus, a cloud DVR service provider can take many copies of the same file stored in the cloud and save storage space by compressing those copies while still maintaining their status as distinct copies, one per user. Vector quantization is used for compressing already-compressed video streams (e.g., MPEG streams). As vector quantization is a lossy compression scheme, the residual vector has to be stored to regenerate the original video stream at the decoding (playback) node. Entropy coding schemes like Arithmetic or Huffman coding can be used to compress the residual vectors. Additional strategies can be implemented to further optimize this residual compression. In some embodiments, the techniques operate to provide a 25-50% improvement in compression. Storage space is thus more efficiently used and video transmission may be faster in some cases.Type: ApplicationFiled: June 4, 2021Publication date: September 23, 2021Applicant: Adobe Inc.Inventors: VISWANATHAN SWAMINATHAN, SAAYAN MITRA, AKSHAY MALHOTRA
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Publication number: 20210295150Abstract: A system and method is disclosed for classifying time-series data provided to a machine-learning model from a continuous sensor signal. The data may be “windowed” or “divided” into a smaller data segment using a first stage classifier where an “event of interest” may be identified. The first stage classifier may employ an algorithm that prohibits false negative identifications. The data segment detected as including an event of interest may then be transmitted to a second stage classifier operable to performs a full classification on the data segment. The multi-stage network may require less power and a less complex structure.Type: ApplicationFiled: March 20, 2020Publication date: September 23, 2021Inventors: Thomas ROCZNIK, Akshay MALHOTRA, Christian PETERS, Rudolf BICHLER, Robert DUERICHEN
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Publication number: 20210272341Abstract: Generating images and videos depicting a human subject wearing textually defined attire is described. An image generation system receives a two-dimensional reference image depicting a person and a textual description describing target clothing in which the person is to be depicted as wearing. To maintain a personal identity of the person, the image generation system implements a generative model, trained using both discriminator loss and perceptual quality loss, which is configured to generate images from text. In some implementations, the image generation system is configured to train the generative model to output visually realistic images depicting the human subject in the target clothing. The image generation system is further configured to apply the trained generative model to process individual frames of a reference video depicting a person and output frames depicting the person wearing textually described target clothing.Type: ApplicationFiled: February 28, 2020Publication date: September 2, 2021Applicant: Adobe Inc.Inventors: Viswanathan Swaminathan, Gang Wu, Akshay Malhotra
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Publication number: 20210218414Abstract: A system and method for generating and using fixed-point operations for neural networks includes converting floating-point weighting factors into fixed-point weighting factors using a scaling factor. The scaling factor is defined to minimize a cost function and the scaling factor is derived from a set of multiples of a predetermined base. The set of possible scaling function is defined to reduce the computational effort for evaluating the cost function for each of a number of possible scaling factors. The system and method may be implemented in one or more controllers that are programmed to execute the logic.Type: ApplicationFiled: January 10, 2020Publication date: July 15, 2021Inventors: Akshay MALHOTRA, Thomas ROCZNIK, Christian PETERS
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Patent number: 11032578Abstract: Residual vectors are compressed in a lossless compression scheme suitable for cloud DVR video content applications. Thus, a cloud DVR service provider can take many copies of the same file stored in the cloud and save storage space by compressing those copies while still maintaining their status as distinct copies, one per user. Vector quantization is used for compressing already-compressed video streams (e.g., MPEG streams). As vector quantization is a lossy compression scheme, the residual vector has to be stored to regenerate the original video stream at the decoding (playback) node. Entropy coding schemes like Arithmetic or Huffman coding can be used to compress the residual vectors. Additional strategies can be implemented to further optimize this residual compression. In some embodiments, the techniques operate to provide a 25-50% improvement in compression. Storage space is thus more efficiently used and video transmission may be faster in some cases.Type: GrantFiled: June 27, 2018Date of Patent: June 8, 2021Assignee: Adobe Inc.Inventors: Viswanathan Swaminathan, Saayan Mitra, Akshay Malhotra
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Publication number: 20180310029Abstract: Residual vectors are compressed in a lossless compression scheme suitable for cloud DVR video content applications. Thus, a cloud DVR service provider can take many copies of the same file stored in the cloud and save storage space by compressing those copies while still maintaining their status as distinct copies, one per user. Vector quantization is used for compressing already-compressed video streams (e.g., MPEG streams). As vector quantization is a lossy compression scheme, the residual vector has to be stored to regenerate the original video stream at the decoding (playback) node. Entropy coding schemes like Arithmetic or Huffman coding can be used to compress the residual vectors. Additional strategies can be implemented to further optimize this residual compression. In some embodiments, the techniques operate to provide a 25-50% improvement in compression. Storage space is thus more efficiently used and video transmission may be faster in some cases.Type: ApplicationFiled: June 27, 2018Publication date: October 25, 2018Applicant: Adobe Systems IncorporatedInventors: VISWANATHAN SWAMINATHAN, SAAYAN MITRA, AKSHAY MALHOTRA
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Patent number: 10063892Abstract: Residual vectors are compressed in a lossless compression scheme suitable for cloud DVR video content applications. Thus, a cloud DVR service provider can take many copies of the same file stored in the cloud and save storage space by compressing those copies while still maintaining their status as distinct copies, one per user. Vector quantization is used for compressing already-compressed video streams (e.g., MPEG streams). As vector quantization is a lossy compression scheme, the residual vector has to be stored to regenerate the original video stream at the decoding (playback) node. Entropy coding schemes like Arithmetic or Huffman coding can be used to compress the residual vectors. Additional strategies can be implemented to further optimize this residual compression. In some embodiments, the techniques operate to provide a 25-50% improvement in compression. Storage space is thus more efficiently used and video transmission may be faster in some cases.Type: GrantFiled: December 10, 2015Date of Patent: August 28, 2018Assignee: Adobe Systems IncorporatedInventors: Viswanathan Swaminathan, Saayan Mitra, Akshay Malhotra
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Patent number: 10027992Abstract: Residual vectors are compressed in a lossless compression scheme suitable for cloud DVR video content applications. Thus, a cloud DVR service provider can take many copies of the same file stored in the cloud and save storage space by compressing those copies while still maintaining their status as distinct copies, one per user. Vector quantization is used for compressing already-compressed video streams (e.g., MPEG streams). As vector quantization is a lossy compression scheme, the residual vector has to be stored to regenerate the original video stream at the decoding (playback) node. Entropy coding schemes like Arithmetic or Huffman coding can be used to compress the residual vectors. Additional strategies can be implemented to further optimize this residual compression. In some embodiments, the techniques operate to provide a 25-50% improvement in compression. Storage space is thus more efficiently used and video transmission may be faster in some cases.Type: GrantFiled: December 10, 2015Date of Patent: July 17, 2018Assignee: Adobe Systems IncorporatedInventors: Viswanathan Swaminathan, Saayan Mitra, Akshay Malhotra
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Publication number: 20170171564Abstract: Techniques are disclosed to compress residual vectors in a lossless compression scheme suitable for cloud DVR video content applications. Thus, a cloud DVR service provider can take many copies of the same file stored in the cloud and save storage space by compressing those copies while still maintaining their status as distinct copies, one per user. Vector quantization is used for compressing already-compressed video streams (e.g., MPEG streams). As vector quantization is a lossy compression scheme, the residual vector has to be stored to regenerate the original video stream at the decoding (playback) node. Entropy coding schemes like Arithmetic or Huffman coding can be used to compress the residual vectors. Additional strategies can be implemented to further optimize this residual compression. In some embodiments, the techniques operate to provide a 25-50% improvement in compression. Storage space is thus more efficiently used and video transmission may be faster in some cases.Type: ApplicationFiled: December 10, 2015Publication date: June 15, 2017Applicant: Adobe Systems IncorporatedInventors: VISWANATHAN SWAMINATHAN, SAAYAN MITRA, AKSHAY MALHOTRA