Distance detection based on chromatic aberration

    公开(公告)号:US10573024B1

    公开(公告)日:2020-02-25

    申请号:US15243768

    申请日:2016-08-22

    Abstract: Described herein are systems and methods of determining a distance between an object depicted in an image and an imaging device that captured that image. In particular, the disclosure discusses that an image may be separated into multiple derivative images, each of which is associated with a different wavelength of light. In some embodiments, an image may be separated into images associated with wavelengths of primary colors (e.g., red, green, and blue). Once separate images have been created, a sharpness value may be determined for each image. A distance between the object and the imaging device may then be calculated based on sharpness values associated with each of the separate images.

    Location marker with lights
    4.
    发明授权

    公开(公告)号:US10176722B1

    公开(公告)日:2019-01-08

    申请号:US15250806

    申请日:2016-08-29

    Abstract: A location marker that may be used to provide information to a vehicle, such as an unmanned aerial vehicle (UAV). The location marker may include a plurality of lights that may be individually sequenced on and off at different times to create a time domain signal sequence that is readable by the vehicle. The lights may provide information in various different ways. The specific lights that are illuminated at a certain time may form a light pattern that includes or is associated with information. Different light patterns may be displayed over time to provide different information to the vehicle. In some embodiments, the amount of time that a light is on or off (or both) may provide information as a time domain signal sequence (e.g., flashing lights) to the vehicle. In various embodiments, the location marker may include retroreflectors arranged in a pattern used to identify the location marker.

    Location marker with retroreflectors

    公开(公告)号:US10032384B1

    公开(公告)日:2018-07-24

    申请号:US15250778

    申请日:2016-08-29

    Abstract: A location marker that may be used to provide information to a vehicle, such as an unmanned aerial vehicle (UAV). The location marker may include a plurality of retroreflectors that may form a pattern readable by a vehicle or other device. The pattern may be read to extract an identifier of a location, such as an address or an identifier of a person. A global positioning system (GPS) device may transmit a general location of the location marker to the vehicle, while the location marker may provide a unique visual location identifier to a device within visual range of the location marker. In some embodiments, the location marker may also include lights that may be individually sequenced on and off at different times to create a time domain signal sequence that is readable by the vehicle.

    Flare detection and avoidance in stereo vision systems

    公开(公告)号:US10538326B1

    公开(公告)日:2020-01-21

    申请号:US15253339

    申请日:2016-08-31

    Abstract: This disclosure is directed to monitoring exposure levels for individual cameras of a stereo camera system to reduce unwanted lens flaring which may disrupt stereo vision capabilities of an unmanned aerial vehicle (UAV). The UAV may identify lens flaring by monitoring histogram data received from the cameras and then mitigate the lens flaring by performing aerial maneuvers with respect to the light source and/or moving camera componentry such as deploying a lens hood. The UAV may also identify lens flaring patterns that on a camera's sensor and determine a location of a peripheral light source based on these patterns. The UAV may then deploy a visor between the location of the peripheral light source and the cameras.

    Processing images to remove precipitation

    公开(公告)号:US10182225B1

    公开(公告)日:2019-01-15

    申请号:US15253602

    申请日:2016-08-31

    Abstract: Images captured by a camera system can be processed to detect precipitation in one or more of the images, and to generate a reconstructed image(s) without the precipitation, or with a reduced amount of the precipitation. Detection of precipitation can be based on a difference between a first feature in a first image and a second feature in a second image that corresponds to the first feature, where the first and second images were captured by different cameras at different times. A determination as to whether precipitation is present in the first image and the second image can be based at least in part on a disparity between the first feature and the second feature.

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