MAPPING AND TRACKING SYSTEM
First Claim
1. A method for real-time tracking of features, the method comprising:
- acquiring a collection of images and one or more subsequent collections of images to create a three-dimensional space, wherein the collection of images and the one or more subsequent collections of images are substantially simultaneously captured from multiple sources;
identifying a candidate feature in the three-dimensional space for tracking; and
tracking the candidate feature in the three-dimensional space over time.
2 Assignments
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Accused Products
Abstract
LK-SURF, Robust Kalman Filter, HAR-SLAM, and Landmark Promotion SLAM methods are disclosed. LK-SURF is an image processing technique that combines Lucas-Kanade feature tracking with Speeded-Up Robust Features to perform spatial and temporal tracking using stereo images to produce 3D features can be tracked and identified. The Robust Kalman Filter is an extension of the Kalman Filter algorithm that improves the ability to remove erroneous observations using Principal Component Analysis and the X84 outlier rejection rule. Hierarchical Active Ripple SLAM is a new SLAM architecture that breaks the traditional state space of SLAM into a chain of smaller state spaces, allowing multiple tracked objects, multiple sensors, and multiple updates to occur in linear time with linear storage with respect to the number of tracked objects, landmarks, and estimated object locations. In Landmark Promotion SLAM, only reliable mapped landmarks are promoted through various layers of SLAM to generate larger maps.
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Citations
61 Claims
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1. A method for real-time tracking of features, the method comprising:
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acquiring a collection of images and one or more subsequent collections of images to create a three-dimensional space, wherein the collection of images and the one or more subsequent collections of images are substantially simultaneously captured from multiple sources; identifying a candidate feature in the three-dimensional space for tracking; and tracking the candidate feature in the three-dimensional space over time. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17)
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18. A method for filtering outlier features from captured high-dimensional observations, the method comprising:
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mapping a high-dimensional feature into a one-dimensional space; and applying an outlier rejection rule in the one-dimensional space to remove the mapped feature. - View Dependent Claims (19, 20, 21, 22)
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23. A method for managing objects in a multi-dimensional space when the objects are no longer visible in a collection of images captured from the multi-dimensional space over time, the method comprising:
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identifying one or more objects visible in a first image among the collection of images; adding the identified objects to a first list of tracked identified objects; tracking the identified objects from the first list of objects in one or more subsequent images among the collection of images, the one or more subsequent images being captured after capturing the first image; determining whether the tracked identified objects are absent in the one or more subsequent images; and removing, based on the determination, the tracked identified objects from the first list. - View Dependent Claims (24, 25, 26, 27, 28, 29, 30)
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31. A method for creating a connected graph, the method comprises:
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associating a first pose of a first sensor with landmarks detected in a first image from a multi-dimensional space acquired by the first sensor; adding the first pose and the landmarks to a state space; determining that the landmarks are absent from a second image from the multi-dimensional space acquired by the first sensor in a second pose; removing the landmarks from the state space based on the determination; correlating the first and second poses; and correlating the landmarks with the second pose. - View Dependent Claims (32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49)
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50. A method for promoting high-dimensional objects through various layers of a simultaneous location and mapping system, the method comprising:
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determining at a first level of the system a first set of reliable high-dimensional objects associated with a first mapped region; and promoting the first set of reliable high-dimensional objects to a second level of the system, wherein the second level combines the first set of reliable high-dimensional objects with a second set of reliable high-dimensional objects associated with a second mapped region to produce a map corresponding to a region larger than each of the first and second mapped regions.
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51. A system for creating a map of a high-dimensional area and locating the system on the map, the system comprising:
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a processor; and a memory communicatively coupled to the processor when the system is operational, the memory bearing processor instructions that, when executed on the processor, cause the system to at least; create a state associated with stereo images of the area to be mapped; process a first stereo image to identify a visual feature within the area, wherein the first stereo image is associated with a first pose of the system; process a second stereo image to determine whether the visual feature is absent from the area in the second stereo image, wherein the second stereo image is associated with a second pose of the system; remove, based on the determination, the first pose and the visual feature from the state and send the first pose and the visual feature to a mapping module configured to maintain a structure that correlates poses and visual features; and create a map of the area and at least one location of the system on the map. - View Dependent Claims (52, 53, 54)
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55. A computer readable storage medium having stored thereon instructions that, when executed by a processor, cause the processor to:
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receive a visual feature, wherein the visual feature is identified in a three-dimensional image and is associated with a pose, wherein the pose is associated with a first device that captured the three-dimensional image; compare the visual feature to visual features comprised in a database to find a match; transmit the visual feature and the match to a module configured to maintain a map that correlates poses and visual features; determine whether the visual feature is over a quality threshold; and update the visual feature with information received from a second device capturing three-dimensional images. - View Dependent Claims (56, 57, 58, 59, 60, 61)
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Specification