Patents by Inventor Lo Po Tsui
Lo Po Tsui 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: 20250103844Abstract: Aspects of the disclosure provide for automatically generating labels for sensor data. For instance, first sensor data for a vehicle may be identified. This first sensor data may have been captured by a first sensor of the vehicle at a first location during a first point in time and may be associated with a first label for an object. Second sensor data for the vehicle may be identified. The second sensor data may have been captured by a second sensor of the vehicle at a second location at a second point in time outside of the first point in time. The second location is different from the first location. A determination may be made as to whether the object is a static object. Based on the determination that the object is a static object, the first label may be used to automatically generate a second label for the second sensor data.Type: ApplicationFiled: December 9, 2024Publication date: March 27, 2025Inventors: Justin Thorsen, Changchang Wu, Alper Ayvaci, Tiffany Chen, Lo Po Tsui, Zhinan Xu, Chen Wu, Sean Rafferty
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Patent number: 12211269Abstract: Methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for generating and editing object track labels for objects detected in video data. One of the methods includes obtaining a video segment comprising multiple image frames associated with multiple time points; obtaining object track data specifying a set of object tracks; providing, for presentation to a user, a user interface for modifying the object track data, the user interface displaying object timeline representations of the object tracks; receiving one or more user inputs that indicate one or more modifications to the object timeline representations; updating the object timeline representations displayed in the timeline display area; and updating the object track data according to the updated object timeline representations.Type: GrantFiled: May 7, 2021Date of Patent: January 28, 2025Assignee: Waymo LLCInventors: Yulai Shen, Henrik Kretzschmar, Jeffrey Sham, Jeffrey Carlson, Lo Po Tsui, Dragomir Anguelov
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Patent number: 12204969Abstract: Aspects of the disclosure provide for automatically generating labels for sensor data. For instance, first sensor data, for a vehicle may be identified. This first sensor data may have been captured by a first sensor of the vehicle at a first location during a first point in time and may be associated with a first label for an object. Second sensor data for the vehicle may be identified. The second sensor data may have been captured by a second sensor of the vehicle at a second location at a second point in time outside of the first point in time. The second location is different from the first location. A determination may be made as to whether the object is a static object. Based on the determination that the object is a static object, the first label may be used to automatically generate a second label for the second sensor data.Type: GrantFiled: August 23, 2022Date of Patent: January 21, 2025Assignee: Waymo LLCInventors: Justin Thorsen, Changchang Wu, Alper Ayvaci, Tiffany Chen, Lo Po Tsui, Zhinan Xu, Chen Wu, Sean Rafferty
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Publication number: 20230099920Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a classifier to detect open vehicle doors. One of the methods includes obtaining a plurality of initial training examples, each initial training example comprising (i) a sensor sample from a collection of sensor samples and (ii) data classifying the sensor sample as characterizing a vehicle that has an open door; generating a plurality of additional training examples, comprising, for each initial training example: identifying, from the collection of sensor samples, one or more additional sensor samples that were captured less than a threshold amount of time before the sensor sample in the initial training example was captured; and training the machine learning classifier on first training data that includes the initial training examples and the additional training examples to generate updated weights for the machine learning classifier.Type: ApplicationFiled: November 28, 2022Publication date: March 30, 2023Inventors: Junhua Mao, Lo Po Tsui, Congcong Li, Edward Stephen Walker, JR.
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Publication number: 20230046289Abstract: Aspects of the disclosure provide for automatically generating labels for sensor data. For instance, first sensor data, for a vehicle may be identified. This first sensor data may have been captured by a first sensor of the vehicle at a first location during a first point in time and may be associated with a first label for an object. Second sensor data for the vehicle may be identified. The second sensor data may have been captured by a second sensor of the vehicle at a second location at a second point in time outside of the first point in time. The second location is different from the first location. A determination may be made as to whether the object is a static object. Based on the determination that the object is a static object, the first label may be used to automatically generate a second label for the second sensor data.Type: ApplicationFiled: August 23, 2022Publication date: February 16, 2023Inventors: Justin Thorsen, Changchang Wu, Alper Ayvaci, Tiffany Chen, Lo Po Tsui, Zhinan Xu, Chen Wu, Sean Rafferty
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Patent number: 11556744Abstract: Aspects of the disclosure relate to training a labeling model to automatically generate labels for objects detected in a vehicle's environment. In this regard, one or more computing devices may receive sensor data corresponding to a series of frames perceived by the vehicle, each frame being captured at a different time point during a trip of the vehicle. The computing devices may also receive bounding boxes generated by a first labeling model for objects detected in the series of frames. The computing devices may receive user inputs including an adjustment to at least one of the bounding boxes, the adjustment corrects a displacement of the at least one of the bounding boxes caused by a sensing inaccuracy. The computing devices may train a second labeling model using the sensor data, the bounding boxes, and the adjustment to increase accuracy of the second labeling model when automatically generating bounding boxes.Type: GrantFiled: December 9, 2020Date of Patent: January 17, 2023Assignee: Waymo LLCInventors: Aditya Joshi, Ingrid Fiedler, Lo Po Tsui
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Publication number: 20220391616Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium that validates labels associated with sensor measurements of a scene in an environment. One of the methods includes receiving data representing a sensor measurement of a scene in an environment generated by one or more sensors. The sensor measurement can be associated with one or more labels, and each label can identify a portion of the sensor measurement that has been classified as measuring an object in the environment. For each of the labels, a determination can be made as to whether the label satisfies each of the validation criteria. Each validation criterion can measure whether one or more characteristics of the label are consistent with one or more characteristics of real-world objects in the environment.Type: ApplicationFiled: June 7, 2021Publication date: December 8, 2022Inventors: Lo Po Tsui, Allen Minich, Megan Van Welie, Neil Barooah, Dragomir Anguelov
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Patent number: 11514310Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a classifier to detect open vehicle doors. One of the methods includes obtaining a plurality of initial training examples, each initial training example comprising (i) a sensor sample from a collection of sensor samples and (ii) data classifying the sensor sample as characterizing a vehicle that has an open door; generating a plurality of additional training examples, comprising, for each initial training example: identifying, from the collection of sensor samples, one or more additional sensor samples that were captured less than a threshold amount of time before the sensor sample in the initial training example was captured; and training the machine learning classifier on first training data that includes the initial training examples and the additional training examples to generate updated weights for the machine learning classifier.Type: GrantFiled: December 21, 2018Date of Patent: November 29, 2022Assignee: Waymo LLCInventors: Junhua Mao, Lo Po Tsui, Congcong Li, Edward Stephen Walker, Jr.
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Publication number: 20220358314Abstract: Methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for generating and editing object track labels for objects detected in video data. One of the methods includes obtaining a video segment comprising multiple image frames associated with multiple time points; obtaining object track data specifying a set of object tracks; providing, for presentation to a user, a user interface for modifying the object track data, the user interface displaying object timeline representations of the object tracks; receiving one or more user inputs that indicate one or more modifications to the object timeline representations; updating the object timeline representations displayed in the timeline display area; and updating the object track data according to the updated object timeline representations.Type: ApplicationFiled: May 7, 2021Publication date: November 10, 2022Inventors: Yulai Shen, Henrik Kretzschmar, Jeffrey Sham, Jeffrey Carlson, Lo Po Tsui, Dragomir Anguelov
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Patent number: 11475263Abstract: Aspects of the disclosure provide for automatically generating labels for sensor data. For instance, first sensor data for a vehicle may be identified. This first sensor data may have been captured by a first sensor of the vehicle at a first location during a first point in time and may be associated with a first label for an object. Second sensor data for the vehicle may be identified. The second sensor data may have been captured by a second sensor of the vehicle at a second location at a second point in time outside of the first point in time. The second location is different from the first location. A determination may be made as to whether the object is a static object. Based on the determination that the object is a static object, the first label may be used to automatically generate a second label for the second sensor data.Type: GrantFiled: March 24, 2020Date of Patent: October 18, 2022Assignee: Waymo LLCInventors: Justin Thorsen, Changchang Wu, Alper Ayvaci, Tiffany Chen, Lo Po Tsui, Zhinan Xu, Chen Wu, Sean Rafferty
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Publication number: 20210303956Abstract: Aspects of the disclosure provide for automatically generating labels for sensor data. For instance, first sensor data for a first vehicle may be identified. This first sensor data may have been captured by a first sensor of the vehicle at a first location during a first point in time and may be associated with a first label for an object. Second sensor data for a vehicle may be identified. The second sensor data may have been captured by a second sensor of the vehicle at a second location at a second point in time outside of the first point in time. The second location is different from the first location. The object is a static object may be determined. Based on the determination that the object is a static object, the first label may be used to automatically generate a second label for the second sensor data.Type: ApplicationFiled: March 24, 2020Publication date: September 30, 2021Inventors: Justin Thorsen, Changchang Wu, Alper Ayvaci, Tiffany Chen, Lo Po Tsui, Zhinan Xu, Chen Wu, Sean Rafferty
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Patent number: 10963734Abstract: Aspects of the disclosure relate to facilitating review of labels. For instance, a first type of label for a first set of labels and a second type of label for a second set of labels may be received. The first set of labels may be generated by a first labeling source and may classify one or more objects captured by a sensor of a vehicle. The second set of labels may be generated by a second labeling source different from the first labeling source and may classify the one or more objects. A search is conducted for objects associated with both the first type of labels for the first set of labels and the second type of label for the second set of labels in order to identify search results. The histograms may be generated from the search results and histograms may be provided for display to a human operator.Type: GrantFiled: October 18, 2019Date of Patent: March 30, 2021Assignee: Waymo LLCInventors: Jiajing Wang, Chi Zeng, Lorena Zalles, Lo Po Tsui, Heidi Lam
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Patent number: 10891518Abstract: Aspects of the disclosure relate to training a labeling model to automatically generate labels for objects detected in a vehicle's environment. In this regard, one or more computing devices may receive sensor data corresponding to a series of frames perceived by the vehicle, each frame being captured at a different time point during a trip of the vehicle. The computing devices may also receive bounding boxes generated by a first labeling model for objects detected in the series of frames. The computing devices may receive user inputs including an adjustment to at least one of the bounding boxes, the adjustment corrects a displacement of the at least one of the bounding boxes caused by a sensing inaccuracy. The computing devices may train a second labeling model using the sensor data, the bounding boxes, and the adjustment to increase accuracy of the second labeling model when automatically generating bounding boxes.Type: GrantFiled: December 14, 2018Date of Patent: January 12, 2021Inventors: Aditya Joshi, Ingrid Fiedler, Lo Po Tsui
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Patent number: 10699167Abstract: Aspects of the disclosure relate to generating a grid or a visual list to facilitate operator review of labels. The system receives a first set of labels generated by a first labeling source and a second set of labels generated by a second labeling source. The first set of labels and the second set of labels each classify one or more objects perceived in one or more scenes captured by a sensor of a vehicle, such that each of the one or more objects has a corresponding first label and a corresponding second label. The system determines discrepancies between the corresponding first label and the corresponding second label for each of the one or more objects, and generates a grid or a visual list using the determined discrepancies. The system provides the grid or the visual list for display to a human operator.Type: GrantFiled: October 19, 2018Date of Patent: June 30, 2020Assignee: Waymo LLCInventors: Jonathan Baldwin Dowdall, Nafees Ahmed, Lo Po Tsui, Peter Morton
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Publication number: 20200202209Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a classifier to detect open vehicle doors. One of the methods includes obtaining a plurality of initial training examples, each initial training example comprising (i) a sensor sample from a collection of sensor samples and (ii) data classifying the sensor sample as characterizing a vehicle that has an open door; generating a plurality of additional training examples, comprising, for each initial training example: identifying, from the collection of sensor samples, one or more additional sensor samples that were captured less than a threshold amount of time before the sensor sample in the initial training example was captured; and training the machine learning classifier on first training data that includes the initial training examples and the additional training examples to generate updated weights for the machine learning classifier.Type: ApplicationFiled: December 21, 2018Publication date: June 25, 2020Inventors: Junhua Mao, Lo Po Tsui, Congcong Li, Edward Stephen Walker, JR.