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公开(公告)号：US20200233430A1
公开(公告)日：2020-07-23
申请号：US16837017
申请日：2020-04-01
Applicant: Waymo LLC
Inventor： Wan-Yen Lo , David Ian Franklin Ferguson , Abhijit Ogale
Abstract: A computing device of a first vehicle may receive a first image and a second image of a second vehicle having flashing light signals. The computing device may determine, in the first image and the second image, an image region that bounds the second vehicle such that the image region substantially encompasses the second vehicle. The computing device may determine a polar grid that partitions the image region in the first image and the second image into polar bins, and identify portions of image data exhibiting a change in color and a change in brightness between the first image and the second image. The computing device may determine a type of the flashing light signals and a type of the second vehicle; and accordingly provide instructions to control the first vehicle.
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公开(公告)号：US20190318207A1
公开(公告)日：2019-10-17
申请号：US16447842
申请日：2019-06-20
Applicant: Waymo LLC
Inventor： Wan-Yen Lo , Abhijit Ogale , Yang Gao
Abstract: In some implementations, an image classification system of an autonomous or semi-autonomous vehicle is capable of improving multi-object classification by reducing repeated incorrect classification of objects that are considered rarely occurring objects. The system can include a common instance classifier that is trained to identify and recognize general objects (e.g., commonly occurring objects and rarely occurring objects) as belonging to specified object categories, and a rare instance classifier that is trained to compute one or more rarity scores representing likelihoods that an input image is correctly classified by the common instance classifier. The output of the rare instance classifier can be used to adjust the classification output of the common instance classifier such that the likelihood of input images being incorrectly classified is reduced.
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公开(公告)号：US10346724B2
公开(公告)日：2019-07-09
申请号：US15630275
申请日：2017-06-22
Applicant: Waymo LLC
Inventor： Wan-Yen Lo , Abhijit Ogale , Yang Gao
Abstract: In some implementations, an image classification system of an autonomous or semi-autonomous vehicle is capable of improving multi-object classification by reducing repeated incorrect classification of objects that are considered rarely occurring objects. The system can include a common instance classifier that is trained to identify and recognize general objects (e.g., commonly occurring objects and rarely occurring objects) as belonging to specified object categories, and a rare instance classifier that is trained to compute one or more rarity scores representing likelihoods that an input image is correctly classified by the common instance classifier. The output of the rare instance classifier can be used to adjust the classification output of the common instance classifier such that the likelihood of input images being incorrectly classified is reduced.
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公开(公告)号：US10168712B1
公开(公告)日：2019-01-01
申请号：US15671316
申请日：2017-08-08
Applicant: Waymo LLC
Inventor： Wan-Yen Lo , David Ian Franklin Ferguson , Abhijit Ogale
Abstract: A computing device of a first vehicle may receive a first image and a second image of a second vehicle having flashing light signals. The computing device may determine, in the first image and the second image, an image region that bounds the second vehicle such that the image region substantially encompasses the second vehicle. The computing device may determine a polar grid that partitions the image region in the first image and the second image into polar bins, and identify portions of image data exhibiting a change in color and a change in brightness between the first image and the second image. The computing device may determine a type of the flashing light signals and a type of the second vehicle; and accordingly provide instructions to control the first vehicle.
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公开(公告)号：US09892327B2
公开(公告)日：2018-02-13
申请号：US15331079
申请日：2016-10-21
Applicant: Waymo LLC
Inventor： Abhijit Ogale , Dave Ferguson
CPC classification number: G06K9/00791 , B60R1/00 , B60R2300/80 , G05D1/0088 , G05D1/0246 , G06K9/00825 , G06K9/4604 , G06K9/4652 , G06K9/4661 , H04N5/2353
Abstract: An autonomous vehicle is configured to detect an active turn signal indicator on another vehicle. An image-capture device of the autonomous vehicle captures an image of a field of view of the autonomous vehicle. The autonomous vehicle captures the image with a short exposure to emphasize objects having brightness above a threshold. Additionally, a bounding area for a second vehicle located within the image is determined. The autonomous vehicle identifies a group of pixels within the bounding area based on a first color of the group of pixels. The autonomous vehicle also calculates an oscillation of an intensity of the group of pixels. Based on the oscillation of the intensity, the autonomous vehicle determines a likelihood that the second vehicle has a first active turn signal. Additionally, the autonomous vehicle is controlled based at least on the likelihood that the second vehicle has a first active turn signal.
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Patent Agency Ranking
公开(公告)号：US09857798B2
公开(公告)日：2018-01-02
申请号：US15134570
申请日：2016-04-21
Applicant: Waymo LLC
Inventor： Abhijit Ogale
CPC classification number: G05D1/0231 , B60W30/17 , B60W2420/42 , G06K9/00791 , G06K9/00805 , G06K9/3241 , G06K9/6293 , G06K2209/23
Abstract: The present disclosure is directed to an autonomous vehicle having a vehicle control system. The vehicle control system includes a vehicle detection system. The vehicle detection system includes receiving an image of a field of view of the vehicle and identifying a region-pair in the image with a sliding-window filter. The region-pair is made up of a first region and a second region. Each region is determined based on a color of pixels within the sliding-window filter. The vehicle detection system also determines a potential second vehicle in the image based on the region-pair. In response to determining the potential second vehicle in the image, the vehicle detection system performs a multi-stage classification of the image to determine whether the second vehicle is present in the image. Additionally, the vehicle detection system provides instructions to control the first vehicle based at least on the determined second vehicle.
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公开(公告)号：US12019443B2
公开(公告)日：2024-06-25
申请号：US17452483
申请日：2021-10-27
Applicant: Waymo LLC
Inventor： David Ian Ferguson , Abhijit Ogale
CPC classification number: G05D1/0088 , B60W30/00 , G01S13/02 , G01S17/02 , G01S19/13 , G05D1/0231 , G05D1/0246 , G06V20/58 , G06V20/584
Abstract: Methods and systems for the use of detected objects for image processing are described. A computing device autonomously controlling a vehicle may receive images of the environment surrounding the vehicle from an image-capture device coupled to the vehicle. In order to process the images, the computing device may receive information indicating characteristics of objects in the images from one or more sources coupled to the vehicle. Examples of sources may include RADAR, LIDAR, a map, sensors, a global positioning system (GPS), or other cameras. The computing device may use the information indicating characteristics of the objects to process received images, including determining the approximate locations of objects within the images. Further, while processing the image, the computing device may use information from sources to determine portions of the image to focus upon that may allow the computing device to determine a control strategy based on portions of the image.
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公开(公告)号：US11804049B2
公开(公告)日：2023-10-31
申请号：US17212818
申请日：2021-03-25
Applicant: Waymo LLC
Inventor： Abhijit Ogale , Dave Ferguson
CPC classification number: G06V20/584 , B60R1/00 , G05D1/0088 , G05D1/0246 , G06V20/56 , H04N23/73 , B60R2300/80
Abstract: An autonomous vehicle is configured to detect an active turn signal indicator on another vehicle. An image-capture device of the autonomous vehicle captures an image of a field of view of the autonomous vehicle. The autonomous vehicle captures the image with a short exposure to emphasize objects having brightness above a threshold. Additionally, a bounding area for a second vehicle located within the image is determined. The autonomous vehicle identifies a group of pixels within the bounding area based on a first color of the group of pixels. The autonomous vehicle also calculates an oscillation of an intensity of the group of pixels. Based on the oscillation of the intensity, the autonomous vehicle determines a likelihood that the second vehicle has a first active turn signal. Additionally, the autonomous vehicle is controlled based at least on the likelihood that the second vehicle has a first active turn signal.
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公开(公告)号：US11093799B2
公开(公告)日：2021-08-17
申请号：US16447842
申请日：2019-06-20
Applicant: Waymo LLC
Inventor： Wan-Yen Lo , Abhijit Ogale , Yang Gao
Abstract: In some implementations, an image classification system of an autonomous or semi-autonomous vehicle is capable of improving multi-object classification by reducing repeated incorrect classification of objects that are considered rarely occurring objects. The system can include a common instance classifier that is trained to identify and recognize general objects (e.g., commonly occurring objects and rarely occurring objects) as belonging to specified object categories, and a rare instance classifier that is trained to compute one or more rarity scores representing likelihoods that an input image is correctly classified by the common instance classifier. The output of the rare instance classifier can be used to adjust the classification output of the common instance classifier such that the likelihood of input images being incorrectly classified is reduced.
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公开(公告)号：US11055577B2
公开(公告)日：2021-07-06
申请号：US16447842
申请日：2019-06-20
Applicant: Waymo LLC
Inventor： Wan-Yen Lo , Abhijit Ogale , Yang Gao
Abstract: In some implementations, an image classification system of an autonomous or semi-autonomous vehicle is capable of improving multi-object classification by reducing repeated incorrect classification of objects that are considered rarely occurring objects. The system can include a common instance classifier that is trained to identify and recognize general objects (e.g., commonly occurring objects and rarely occurring objects) as belonging to specified object categories, and a rare instance classifier that is trained to compute one or more rarity scores representing likelihoods that an input image is correctly classified by the common instance classifier. The output of the rare instance classifier can be used to adjust the classification output of the common instance classifier such that the likelihood of input images being incorrectly classified is reduced.
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