Patents by Inventor Atul Kanaujia
Atul Kanaujia 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: 20240087365Abstract: A multisensor processing platform includes, in at least some embodiments, a face detector and embedding network for analyzing unstructured data to detect, identify and track any combination of objects (including people) or activities through computer vision algorithms and machine learning. In some embodiments, the unstructured data is compressed by identifying the appearance of an object across a series of frames of the data, aggregating those appearances and effectively summarizing those appearances of the object by a single representative image displayed to a user for each set of aggregated appearances to enable the user to assess the summarized data substantially at a glance. The data can be filtered into tracklets, groups and clusters, based on system confidence in the identification of the object or activity, to provide multiple levels of granularity.Type: ApplicationFiled: January 19, 2021Publication date: March 14, 2024Applicant: PERCIPIENT.AI INC.Inventors: Timo PYLVAENAEINEN, Craig SENNABAUM, Mike HIGUERA, Ivan KOVTUN, Atul KANAUJIA, Alison HIGUERA, Jerome BERCLAZ, Rajendra SHAH, Balan AYYAR, Vasudev PARAMESWARAN
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Patent number: 11636312Abstract: A computer vision system configured for detection and recognition of objects in video and still imagery in a live or historical setting uses a teacher-student object detector training approach to yield a merged student model capable of detecting all of the classes of objects any of the teacher models is trained to detect. Further, training is simplified by providing an iterative training process wherein a relatively small number of images is labeled manually as initial training data, after which an iterated model cooperates with a machine-assisted labeling process and an active learning process where detector model accuracy improves with each iteration, yielding improved computational efficiency. Further, synthetic data is generated by which an object of interest can be placed in a variety of setting sufficient to permit training of models. A user interface guides the operator in the construction of a custom model capable of detecting a new object.Type: GrantFiled: October 4, 2022Date of Patent: April 25, 2023Assignee: PERCIPIENT.AI INC.Inventors: Vasudev Parameswaran, Atul Kanaujia, Simon Chen, Jerome Berclaz, Ivan Kovtun, Alison Higuera, Vidyadayini Talapady, Derek Young, Balan Ayyar, Rajendra Shah, Timo Pylvanainen
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Publication number: 20230023164Abstract: A computer vision system configured for detection and recognition of objects in video and still imagery in a live or historical setting uses a teacher-student object detector training approach to yield a merged student model capable of detecting all of the classes of objects any of the teacher models is trained to detect. Further, training is simplified by providing an iterative training process wherein a relatively small number of images is labeled manually as initial training data, after which an iterated model cooperates with a machine-assisted labeling process and an active learning process where detector model accuracy improves with each iteration, yielding improved computational efficiency. Further, synthetic data is generated by which an object of interest can be placed in a variety of setting sufficient to permit training of models. A user interface guides the operator in the construction of a custom model capable of detecting a new object.Type: ApplicationFiled: October 4, 2022Publication date: January 26, 2023Applicant: PERCIPIENT.AI INC.Inventors: Vasudev PARAMESWARAN, Atul KANAUJIA, Simon CHEN, Jerome BERCLAZ, Ivan KOVTUN, Alison HIGUERA, Vidyadayini TALAPADY, Derek YOUNG, Balan AYYAR, Rajendra SHAH, Timo PYLVANAINEN
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Publication number: 20230019466Abstract: Systems and methods are disclosed for generating a scaled reconstruction for a consumer product. One method includes receiving digital input comprising a calibration target and an object; defining a three-dimensional coordinate system; positioning the calibration target in the three-dimensional coordinate system; based on the digital input, aligning the object to the calibration target in the three-dimensional coordinate system; and generating a scaled reconstruction of the object based on the alignment of the object to the calibration target in the three-dimensional coordinate system.Type: ApplicationFiled: September 29, 2022Publication date: January 19, 2023Inventors: Eric J. VARADY, Atul Kanaujia
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Patent number: 11495002Abstract: Systems and methods are disclosed for generating a scaled reconstruction for a consumer product. One method includes receiving digital input comprising a calibration target and an object; defining a three-dimensional coordinate system; positioning the calibration target in the three-dimensional coordinate system; based on the digital input, aligning the object to the calibration target in the three-dimensional coordinate system; and generating a scaled reconstruction of the object based on the alignment of the object to the calibration target in the three-dimensional coordinate system.Type: GrantFiled: September 14, 2020Date of Patent: November 8, 2022Assignee: BESPOKE, INC.Inventors: Eric J. Varady, Atul Kanaujia
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Publication number: 20200410775Abstract: Systems and methods are disclosed for generating a scaled reconstruction for a consumer product. One method includes receiving digital input comprising a calibration target and an object; defining a three-dimensional coordinate system; positioning the calibration target in the three-dimensional coordinate system; based on the digital input, aligning the object to the calibration target in the three-dimensional coordinate system; and generating a scaled reconstruction of the object based on the alignment of the object to the calibration target in the three-dimensional coordinate system.Type: ApplicationFiled: September 14, 2020Publication date: December 31, 2020Inventors: Eric J. VARADY, Atul KANAUJIA
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Patent number: 10777018Abstract: Systems and methods are disclosed for generating a scaled reconstruction for a consumer product. One method includes receiving digital input comprising a calibration target and an object; defining a three-dimensional coordinate system; positioning the calibration target in the three-dimensional coordinate system; based on the digital input, aligning the object to the calibration target in the three-dimensional coordinate system; and generating a scaled reconstruction of the object based on the alignment of the object to the calibration target in the three-dimensional coordinate system.Type: GrantFiled: May 16, 2018Date of Patent: September 15, 2020Assignee: Bespoke, Inc.Inventors: Eric J. Varady, Atul Kanaujia
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Patent number: 10186123Abstract: Systems, methods, and manufactures for a surveillance system are provided. The surveillance system includes sensors having at least one non-overlapping field of view. The surveillance system is operable to track a target in an environment using the sensors. The surveillance system is also operable to extract information from images of the target provided by the sensors. The surveillance system is further operable to determine probabilistic confidences corresponding to the information extracted from images of the target. The confidences include at least one confidence corresponding to at least one primitive event. Additionally, the surveillance system is operable to determine grounded formulae by instantiating predefined rules using the confidences. Further, the surveillance system is operable to infer a complex event corresponding to the target using the grounded formulae. Moreover, the surveillance system is operable to provide an output describing the complex event.Type: GrantFiled: March 31, 2015Date of Patent: January 22, 2019Assignee: Avigilon Fortress CorporationInventors: Atul Kanaujia, Tae Eun Choe, Hongli Deng
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Publication number: 20180336737Abstract: Systems and methods are disclosed for generating a scaled reconstruction for a consumer product. One method includes receiving digital input comprising a calibration target and an object; defining a three-dimensional coordinate system; positioning the calibration target in the three-dimensional coordinate system; based on the digital input, aligning the object to the calibration target in the three-dimensional coordinate system; and generating a scaled reconstruction of the object based on the alignment of the object to the calibration target in the three-dimensional coordinate system.Type: ApplicationFiled: May 16, 2018Publication date: November 22, 2018Inventors: Eric J. VARADY, Atul KANAUJIA
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Patent number: 10033979Abstract: A video surveillance system, device and methods may accurately model the shape of a human object monitored by a video stream. 3D human models, such as a coarse 3D human model and a detailed 3D human model may be estimated by mapping individual body part components to a frame. For example, a coarse 3D human model may be obtained by mapping the cylindrical body parts to a plurality of skeleton pose estimates on a part by part basis. A detailed 3D human model may be estimated by mapping detailed human body parts to respective the cylindrical body parts of the coarse 3D human model on a part by part basis. The detailed 3D human model may be used to detect accessories of the human object being monitored, as well as overall dimensions, body part dimensions, age, and gender of the human object being monitored.Type: GrantFiled: March 15, 2013Date of Patent: July 24, 2018Assignee: AVIGILON FORTRESS CORPORATIONInventors: Atul Kanaujia, Niels Haering, Mun Wai Lee
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Publication number: 20160314345Abstract: Methods and systems for facial recognition are provided. The method includes determining a three-dimensional (3D) model of a face of an individual based on different images of the individual. The method also includes extracting two-dimensional (2D) patches from the 3D model. Further, the method includes generating a plurality of signatures of the face using different combinations of the 2D patches, wherein the plurality of signatures correspond to respective views of the 3D model from different angles.Type: ApplicationFiled: July 8, 2016Publication date: October 27, 2016Inventors: Atul Kanaujia, Narayanan Ramanathan, Tae Eun Choe
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Patent number: 9449432Abstract: Methods and systems for facial recognition are provided. The method includes determining a three-dimensional (3D) model of a face of an individual based on different images of the individual. The method also includes extracting two-dimensional (2D) patches from the 3D model. Further, the method includes generating a plurality of signatures of the face using different combinations of the 2D patches, wherein the plurality of signatures correspond to respective views of the 3D model from different angles.Type: GrantFiled: December 19, 2014Date of Patent: September 20, 2016Assignee: AVIGILON FORTRESS CORPORATIONInventors: Atul Kanaujia, Narayanan Ramanathan, Tae Eun Choe
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Publication number: 20150279182Abstract: Systems, methods, and manufactures for a surveillance system are provided. The surveillance system includes sensors having at least one non-overlapping field of view. The surveillance system is operable to track a target in an environment using the sensors. The surveillance system is also operable to extract information from images of the target provided by the sensors. The surveillance system is further operable to determine probablistic confidences corresponding to the information extracted from images of the target. The confidences include at least one confidence corresponding to at least one primitive event. Additionally, the surveillance system is operable to determine grounded formulae by instantiating predefined rules using the confidences. Further, the surveillance system is operable to infer a complex event corresponding to the target using the grounded formulae. Moreover, the surveillance system is operable to provide an output describing the complex event.Type: ApplicationFiled: March 31, 2015Publication date: October 1, 2015Inventors: Atul Kanaujia, Tae Eun Choe, Hongli Deng
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Publication number: 20150178554Abstract: Methods and systems for facial recognition are provided. The method includes determining a three-dimensional (3D) model of a face of an individual based on different images of the individual. The method also includes extracting two-dimensional (2D) patches from the 3D model. Further, the method includes generating a plurality of signatures of the face using different combinations of the 2D patches, wherein the plurality of signatures correspond to respective views of the 3D model from different angles.Type: ApplicationFiled: December 19, 2014Publication date: June 25, 2015Inventors: Atul Kanaujia, Narayanan Ramanathan, Tae Eun Choe
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Patent number: 9014465Abstract: A system and method for tracking features is provided which allows for the tracking of features that move in a series of images. A training set of images is processed to produce clustered shape subspaces corresponding to the set of images, such that non-linear shape manifolds in the images are represented as piecewise, overlapping linear surfaces that are clustered according to similarities in perspectives. A landmark-based training algorithm (e.g., ASM) is applied to the clustered shape subspaces to train a model of the clustered shape subspaces and to create training data. A subsequent image is processed using the training data to identify features in the target image by creating an initial shape, superimposing the initial shape on the target image, and then iteratively deforming the shape in accordance with the model until a final shape is produced corresponding to a feature in the target image.Type: GrantFiled: February 21, 2012Date of Patent: April 21, 2015Assignee: Rutgers, The State University of New JerseyInventors: Dimitris Metaxas, Atul Kanaujia
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Publication number: 20130250050Abstract: A video surveillance system, device and methods may accurately model the shape of a human object monitored by a video stream. 3D human models, such as a coarse 3D human model and a detailed 3D human model may be estimated by mapping individual body part components to a frame. For example, a coarse 3D human model may be obtained by mapping the cylindrical body parts to a plurality of skeleton pose estimates on a part by part basis. A detailed 3D human model may be estimated by mapping detailed human body parts to respective the cylindrical body parts of the coarse 3D human model on a part by part basis. The detailed 3D human model may be used to detect accessories of the human object being monitored, as well as overall dimensions, body part dimensions, age, and gender of the human object being monitored.Type: ApplicationFiled: March 15, 2013Publication date: September 26, 2013Applicant: OBJECTVIDEO, INC.Inventors: Atul Kanaujia, Niels Haering, Mun Wai Lee
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Publication number: 20130022263Abstract: A system and method for tracking features is provided which allows for the tracking of features that move in a series of images A training set of images is processed to produce clustered shape subspaces corresponding to the set of images, such that non-linear shape manifolds in the images are represented as piecewise, overlapping linear surfaces that are clustered according to similarities in perspectives. A landmark-based training algorithm (e.g., ASM) is applied to the clustered shape subspaces to train a model of the clustered shape subspaces and to create training data. A subsequent image is processed using the training data to identify features in the target image by creating an initial shape, superimposing the initial shape on the target image, and then iteratively deforming the shape in accordance with the model until a final shape is produced corresponding to a feature in the target image.Type: ApplicationFiled: February 21, 2012Publication date: January 24, 2013Inventors: Dimitris Metaxas, Atul Kanaujia
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Patent number: 8121347Abstract: A system and method for tracking features, e.g., facial features, is provided, which allows for the tracking of features which move in a series of images and whose shape changes nonlinearly due to perspective projection and complex 3D movements. A training set of images is processed to produce clustered shape subspaces corresponding to the set of images, such that non-linear shape manifolds in the images are represented as piecewise, overlapping linear surfaces that are clustered according to similarities in perspectives. A landmark-based training algorithm (e.g., ASM) is applied to the clustered shape subspaces to train a model of the clustered shape subspaces and to create training data.Type: GrantFiled: December 12, 2007Date of Patent: February 21, 2012Assignee: Rutgers, The State University of New JerseyInventors: Dimitris Metaxas, Atul Kanaujia
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Publication number: 20080187174Abstract: A system and method for tracking features, e.g., facial features, is provided, which allows for the tracking of features which move in a series of images and whose shape changes nonlinearly due to perspective projection and complex 3D movements. A training set of images is processed to produce clustered shape subspaces corresponding to the set of images, such that non-linear shape manifolds in the images are represented as piecewise, overlapping linear surfaces that are clustered according to similarities in perspectives. A landmark-based training algorithm (e.g., ASM) is applied to the clustered shape subspaces to train a model of the clustered shape subspaces and to create training data.Type: ApplicationFiled: December 12, 2007Publication date: August 7, 2008Inventors: Dimitris Metaxas, Atul Kanaujia