System and method for image localization based on semantic segmentation
First Claim
Patent Images
1. A system comprising:
- a data processor; and
an image processing and localization module, executable by the data processor, the image processing and localization module being configured to perform an image processing and localization operation configured to;
receive image data from an image generating device mounted on an autonomous vehicle;
perform semantic segmentation on the received image data to identify and label objects in the image data and produce semantic label image data, wherein the semantic segmentation assigns an object label to each pixel in the image data and the object labels and the velocities of moving or dynamic objects are included in the semantic label image data;
identify extraneous objects in the semantic label image data using the object labels included therein;
identify dynamic objects as extraneous objects in the semantic label image data using the object labels and the velocities of moving or dynamic objects included therein;
remove the extraneous objects from the semantic label image data;
compare the semantic label image data to a baseline semantic label map created from semantic segmentation, wherein the semantic segmentation assigns an object label to each pixel in baseline image data obtained from an image generating device and the object labels are included in the baseline semantic label map; and
determine a vehicle location of the autonomous vehicle based on information in a matching baseline semantic label map.
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Abstract
A system and method for image localization based on semantic segmentation are disclosed. A particular embodiment includes: receiving image data from an image generating device mounted on an autonomous vehicle; performing semantic segmentation or other object detection on the received image data to identify and label objects in the image data and produce semantic label image data; identifying extraneous objects in the semantic label image data; removing the extraneous objects from the semantic label image data; comparing the semantic label image data to a baseline semantic label map; and determining a vehicle location of the autonomous vehicle based on information in a matching baseline semantic label map.
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Citations
20 Claims
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1. A system comprising:
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a data processor; and an image processing and localization module, executable by the data processor, the image processing and localization module being configured to perform an image processing and localization operation configured to; receive image data from an image generating device mounted on an autonomous vehicle; perform semantic segmentation on the received image data to identify and label objects in the image data and produce semantic label image data, wherein the semantic segmentation assigns an object label to each pixel in the image data and the object labels and the velocities of moving or dynamic objects are included in the semantic label image data; identify extraneous objects in the semantic label image data using the object labels included therein; identify dynamic objects as extraneous objects in the semantic label image data using the object labels and the velocities of moving or dynamic objects included therein; remove the extraneous objects from the semantic label image data; compare the semantic label image data to a baseline semantic label map created from semantic segmentation, wherein the semantic segmentation assigns an object label to each pixel in baseline image data obtained from an image generating device and the object labels are included in the baseline semantic label map; and determine a vehicle location of the autonomous vehicle based on information in a matching baseline semantic label map. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A method comprising:
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receiving image data from an image generating device mounted on an autonomous vehicle; performing semantic segmentation on the received image data to identify and label objects in the image data and produce semantic label image data, wherein the semantic segmentation assigns an object label to each pixel in the image data and the object labels and the velocities of moving or dynamic objects are included in the semantic label image data; identifying extraneous objects in the semantic label image data using the object labels included therein; identifying dynamic objects as extraneous objects in the semantic label image data using the object labels and the velocities of moving or dynamic objects included therein; removing the extraneous objects from the semantic label image data; comparing the semantic label image data to a baseline semantic label map created from semantic segmentation, wherein the semantic segmentation assigns an object label to each pixel in baseline image data obtained from an image generating device and the object labels are included in the baseline semantic label map; and determining a vehicle location of the autonomous vehicle based on information in a matching baseline semantic label map. - View Dependent Claims (9, 10, 11, 12, 13, 14)
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15. A non-transitory machine-useable storage medium embodying instructions which, when executed by a machine, cause the machine to:
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receive image data from an image generating device mounted on an autonomous vehicle; perform semantic segmentation on the received image data to identify and label objects in the image data and produce semantic label image data, wherein the semantic segmentation assigns an object label to each pixel in the image data and the object labels and the velocities of moving or dynamic objects are included in the semantic label image data; identify extraneous objects in the semantic label image data using the object labels included therein; identify dynamic objects as extraneous objects in the semantic label image data using the object labels and the velocities of moving or dynamic objects included therein; remove the extraneous objects from the semantic label image data; compare the semantic label image data to a baseline semantic label map created from semantic segmentation, wherein the semantic segmentation assigns an object label to each pixel in baseline image data obtained from an image generating device and the object labels are included in the baseline semantic label map; and determine a vehicle location of the autonomous vehicle based on information in a matching baseline semantic label map. - View Dependent Claims (16, 17, 18, 19, 20)
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Specification