Patents by Inventor Russell P. Bobbitt
Russell P. Bobbitt 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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Patent number: 9443148Abstract: Methods and system are provided for monitoring a queue. A method includes receiving by sensors a non-visual identifier at predefined locations of a queue. Further, the method includes capturing by image capture devices images of an object possessing the non-visual identifier at the predefined locations of the queue. Further, the method includes visually tracking another object in the queue based on transformations of a predefined feature extracted from the images of the object possessing the non-visual identifier at the predefined locations.Type: GrantFiled: March 15, 2013Date of Patent: September 13, 2016Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Ira L. Allen, Russell P. Bobbitt, Rogerio S. Feris, Yun Zhai
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Patent number: 9299162Abstract: Multi-mode video event indexing includes determining a quality of object distinctiveness with respect to images from a video stream input. A high-quality analytic mode is selected from multiple modes and applied to video input images via a hardware device to determine object activity within the video input images if the determined level of detected quality of object distinctiveness meets a threshold level of quality, else a low-quality analytic mode is selected and applied to the video input images via a hardware device to determine object activity within the video input images, wherein the low-quality analytic mode is different from the high-quality analytic mode.Type: GrantFiled: July 31, 2015Date of Patent: March 29, 2016Assignee: International Business Machines CorporationInventors: Russell P. Bobbitt, Lisa M. Brown, Rogerio S. Feris, Arun Hampapur, Yun Zhai
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Publication number: 20160034766Abstract: Transaction units of video data and transaction data captured from different checkout lanes are prioritized as a function of lane priority values of respective ones of the different checkout lanes from which the transaction units are acquired. Each of the checkout lanes has a different lane priority value. The individual transaction units are processed in the prioritized processing order to automatically detect irregular activities indicated by the transaction unit video and the transaction data of the processed individual transaction units.Type: ApplicationFiled: October 16, 2015Publication date: February 4, 2016Inventors: RUSSELL P. BOBBITT, QUANFU FAN, SACHIKO MIYAZAWA, SHARATHCHANDRA U. PANKANTI, YUN ZHAI
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Publication number: 20150356745Abstract: Multi-mode video event indexing includes determining a quality of object distinctiveness with respect to images from a video stream input. A high-quality analytic mode is selected from multiple modes and applied to video input images via a hardware device to determine object activity within the video input images if the determined level of detected quality of object distinctiveness meets a threshold level of quality, else a low-quality analytic mode is selected and applied to the video input images via a hardware device to determine object activity within the video input images, wherein the low-quality analytic mode is different from the high-quality analytic mode.Type: ApplicationFiled: August 19, 2015Publication date: December 10, 2015Inventors: Russell P. Bobbitt, Lisa M. Brown, Rogerio S. Feris, Arun Hampapur, Yun Zhai
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Publication number: 20150339831Abstract: Multi-mode video event indexing includes determining a quality of object distinctiveness with respect to images from a video stream input. A high-quality analytic mode is selected from multiple modes and applied to video input images via a hardware device to determine object activity within the video input images if the determined level of detected quality of object distinctiveness meets a threshold level of quality, else a low-quality analytic mode is selected and applied to the video input images via a hardware device to determine object activity within the video input images, wherein the low-quality analytic mode is different from the high-quality analytic mode.Type: ApplicationFiled: July 31, 2015Publication date: November 26, 2015Inventors: Russell P. Bobbitt, Lisa M. Brown, Rogerio S. Feris, Arun Hampapur, Yun Zhai
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Patent number: 9197868Abstract: Transaction units of video data and transaction data captured from different checkout lanes are prioritized as a function of lane priority values of respective ones of the different checkout lanes from which the transaction units are acquired. Each of the checkout lanes has a different lane priority value. The individual transaction units are processed in the prioritized processing order to automatically detect irregular activities indicated by the transaction unit video and the transaction data of the processed individual transaction units.Type: GrantFiled: September 10, 2013Date of Patent: November 24, 2015Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Russell P. Bobbitt, Quanfu Fan, Sachiko Miyazawa, Sharathchandra U. Pankanti, Yun Zhai
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Publication number: 20150278631Abstract: Machine logic that pre-processes and post-processes images for visual object detection by performing the following steps: receiving a set of image(s); filtering the set of image(s) using a set of multimodal integral filter(s), thereby removing at least a portion of the set of image(s) and resulting in a filtered set of image(s); performing object detection on the filtered set of image(s) to generate a set of object-detected image(s); assembling a first plurality of object-detected image(s) from the set of object-detected image(s); and upon assembling the first plurality of object-detected image(s), performing non-maximum suppression on the assembled first plurality of object-detected image(s).Type: ApplicationFiled: March 23, 2015Publication date: October 1, 2015Inventors: Russell P. Bobbitt, Lisa M. Brown, Rogerio S. Feris, Sharathchandra U. Pankanti, Yun Zhai
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Patent number: 9147259Abstract: Multi-mode video event indexing includes determining a quality of object distinctiveness with respect to images from a video stream input. A high-quality analytic mode is selected from multiple modes and applied to video input images via a hardware device to determine object activity within the video input images if the determined level of detected quality of object distinctiveness meets a threshold level of quality, else a low-quality analytic mode is selected and applied to the video input images via a hardware device to determine object activity within the video input images, wherein the low-quality analytic mode is different from the high-quality analytic mode.Type: GrantFiled: August 21, 2013Date of Patent: September 29, 2015Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Russell P. Bobbitt, Lisa M. Brown, Rogerio S. Feris, Arun Hampapur, Yun Zhai
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Patent number: 9123129Abstract: Multi-mode video event indexing includes determining a quality of object distinctiveness with respect to images from a video stream input. A high-quality analytic mode is selected from multiple modes and applied to video input images via a hardware device to determine object activity within the video input images if the determined level of detected quality of object distinctiveness meets a threshold level of quality, else a low-quality analytic mode is selected and applied to the video input images via a hardware device to determine object activity within the video input images, wherein the low-quality analytic mode is different from the high-quality analytic mode.Type: GrantFiled: August 21, 2013Date of Patent: September 1, 2015Assignee: International Business Machines CorporationInventors: Russell P. Bobbitt, Lisa M. Brown, Rogerio S. Feris, Arun Hampapur, Yun Zhai
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Publication number: 20150242692Abstract: Foreground feature data and motion feature data is determined for frames of video data acquired from a train track area region of interest. The frames are labeled as “train present” if the determined foreground feature data value meets a threshold value, else as “train absent; and as “motion present” if the motion feature data meets a motion threshold, else as “static.” The labels are used to classify segments of the video data comprising groups of consecutive video frames, namely as within a “no train present” segment for groups with “train absent” and “static” labels; within a “train present and in transition” segment for groups “train present” and “motion present” labels; and within a “train present and stopped” segment for groups with “train present” and “static” labels. The presence or motion state of a train at a time of inquiry is thereby determined from the respective segment classification.Type: ApplicationFiled: May 14, 2015Publication date: August 27, 2015Inventors: RUSSELL P. BOBBITT, ROGERIO S. FERIS, YUN ZHAI
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Patent number: 9070020Abstract: Foreground feature data and motion feature data is determined for frames of video data acquired from a train track area region of interest. The frames are labeled as “train present” if the determined foreground feature data value meets a threshold value, else as “train absent”; and as “motion present” if the motion feature data meets a motion threshold, else as “static.” The labels are used to classify segments of the video data comprising groups of consecutive video frames, namely as within a “no train present” segment for groups with “train absent” and “static” labels; within a “train present and in transition” segment for groups “train present” and “motion present” labels; and within a “train present and stopped” segment for groups with “train present” and “static” labels. The presence or motion state of a train at a time of inquiry is thereby determined from the respective segment classification.Type: GrantFiled: August 21, 2012Date of Patent: June 30, 2015Assignee: International Business Machines CorporationInventors: Russell P. Bobbitt, Rogerio S. Feris, Yun Zhai
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Patent number: 9064325Abstract: Multi-mode video event indexing includes determining a quality of object distinctiveness with respect to images from a video stream input. A high-quality analytic mode is selected from multiple modes and applied to video input images via a hardware device to determine object activity within the video input images if the determined level of detected quality of object distinctiveness meets a threshold level of quality, else a low-quality analytic mode is selected and applied to the video input images via a hardware device to determine object activity within the video input images, wherein the low-quality analytic mode is different from the high-quality analytic mode.Type: GrantFiled: August 21, 2013Date of Patent: June 23, 2015Assignee: International Business Machines CorporationInventors: Russell P. Bobbitt, Lisa M. Brown, Rogerio S. Feris, Arun Hampapur, Yun Zhai
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Publication number: 20140267738Abstract: Methods and system are provided for monitoring a queue. A method includes receiving by sensors a non-visual identifier at predefined locations of a queue. Further, the method includes capturing by image capture devices images of an object possessing the non-visual identifier at the predefined locations of the queue. Further, the method includes visually tracking another object in the queue based on transformations of a predefined feature extracted from the images of the object possessing the non-visual identifier at the predefined locations.Type: ApplicationFiled: March 15, 2013Publication date: September 18, 2014Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Ira L. ALLEN, Russell P. BOBBITT, Rogerio S. FERIS, Yun ZHAI
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Patent number: 8761451Abstract: Human behavior is determined by sequential event detection by constructing a temporal-event graph with vertices representing primitive images of images of a video stream, and also of idle states associated with the respective primitive images. A human activity event is determined as a function of a shortest distance path of the temporal-event graph vertices.Type: GrantFiled: August 16, 2013Date of Patent: June 24, 2014Assignee: International Business Machines CorporationInventors: Russell P. Bobbitt, Lei Ding, Quanfu Fan, Sachiko Miyazawa, Sharathchandra U. Pankanti, Yun Zhai
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Patent number: 8744123Abstract: A foreground object blob having a bounding box detected in frame image data is classified by a finite state machine as a background, moving foreground, or temporally static object, namely as the temporally static object when the detected bounding box is distinguished from a background model of a scene image of the video data input and remains static in the scene image for a threshold period. The bounding box is tracked through matching masks in subsequent frame data of the video data input, and the object sub-classified within a visible sub-state, an occluded sub-state, or another sub-state that is not visible and not occluded as a function of a static value ratio. The ratio is a number of pixels determined to be static by tracking in a foreground region of the background model corresponding to the tracked object bounding box over a total number of pixels of the foreground region.Type: GrantFiled: August 29, 2011Date of Patent: June 3, 2014Assignee: International Business Machines CorporationInventors: Russell P. Bobbitt, Quanfu Fan, Zuoxuan Lu, Jiyan Pan, Sharathchandra U. Pankanti
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Patent number: 8694443Abstract: An approach that automatically distinguishes between in-store customers and in-store employees is provided. In one embodiment, there is a learning tool configured to construct a model for an in-store employee; a matching tool configured to match attributes between a particular person and the constructed models for an in-store employee; and a classifying tool configured to classify persons into categories of employees and customers based on amount of matching attributes between a particular person and the model for an in-store employee.Type: GrantFiled: November 3, 2008Date of Patent: April 8, 2014Assignee: International Business Machines CorporationInventors: Russell P. Bobbitt, Quanfu Fan, Sharathchandra U. Pankanti, Akira Yanagawa, Yun Zhai
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Patent number: 8693725Abstract: A method, data processing system, apparatus, and computer program product for monitoring objects. A plurality of images of an area is received. An object in the area is identified from the plurality of images. A plurality of points in a region within the area is identified from a first image in the plurality of images. The plurality of points has a fixed relationship with each other and the region. The object in the area is monitored to determine whether the object has entered the region. A determination that the object has not entered the region is made in response to identifying an absence of a number of the plurality of points in a second image in the plurality of images.Type: GrantFiled: April 19, 2011Date of Patent: April 8, 2014Assignee: International Business Machines CorporationInventors: Russell P. Bobbitt, Frederik C. M. Kjeldsen, Yun Zhai
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Publication number: 20140056479Abstract: Foreground feature data and motion feature data is determined for frames of video data acquired from a train track area region of interest. The frames are labeled as “train present” if the determined foreground feature data value meets a threshold value, else as “train absent; and as “motion present” if the motion feature data meets a motion threshold, else as “static.” The labels are used to classify segments of the video data comprising groups of consecutive video frames, namely as within a “no train present” segment for groups with “train absent” and “static” labels; within a “train present and in transition” segment for groups “train present” and “motion present” labels; and within a “train present and stopped” segment for groups with “train present” and “static” labels. The presence or motion state of a train at a time of inquiry is thereby determined from the respective segment classification.Type: ApplicationFiled: August 21, 2012Publication date: February 27, 2014Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Russell P. Bobbitt, Rogerio S. Feris, Yun Zhai
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Publication number: 20140050356Abstract: Multi-mode video event indexing includes determining a quality of object distinctiveness with respect to images from a video stream input. A high-quality analytic mode is selected from multiple modes and applied to video input images via a hardware device to determine object activity within the video input images if the determined level of detected quality of object distinctiveness meets a threshold level of quality, else a low-quality analytic mode is selected and applied to the video input images via a hardware device to determine object activity within the video input images, wherein the low-quality analytic mode is different from the high-quality analytic mode.Type: ApplicationFiled: August 21, 2013Publication date: February 20, 2014Applicant: International Business Machines CorporationInventors: Russell P. Bobbitt, Lisa M. Brown, Rogerio S. Feris, Arun Hampapur, Yun Zhai
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Publication number: 20140009620Abstract: Transaction units of video data and transaction data captured from different checkout lanes are prioritized as a function of lane priority values of respective ones of the different checkout lanes from which the transaction units are acquired. Each of the checkout lanes has a different lane priority value. The individual transaction units are processed in the prioritized processing order to automatically detect irregular activities indicated by the transaction unit video and the transaction data of the processed individual transaction units.Type: ApplicationFiled: September 10, 2013Publication date: January 9, 2014Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Russell P. Bobbitt, Quanfu Fan, Sachiko Miyazawa, Sharathchandra U. Pankanti, Yun Zhai