Semi-dense depth estimation from a dynamic vision sensor (DVS) stereo pair and a pulsed speckle pattern projector

    公开(公告)号:US11143879B2

    公开(公告)日:2021-10-12

    申请号:US16172473

    申请日:2018-10-26

    Abstract: A method for semi-dense depth estimation includes receiving, at an electronic device, a control signal of a speckle pattern projector (SPP and receiving from each sensor of a dynamic vision sensor (DVS) stereo pair, an event stream of pixel intensity change data, wherein the event stream is time-synchronized with the control signal of the SPP. The method further includes performing projected light filtering on the event stream of pixel intensity change data for each sensor of the DVS stereo pair, to generate synthesized event image data, the synthesized event image data having one or more channels, each channel based on an isolated portion of the event stream of pixel intensity change data and performing stereo matching on at least one channel of the synthesized event image data for each sensor of the DVS stereo pair to generate a depth map for at least a portion of the field of view.

    CMOS-assisted inside-out dynamic vision sensor tracking for low power mobile platforms

    公开(公告)号:US11381741B2

    公开(公告)日:2022-07-05

    申请号:US16953111

    申请日:2020-11-19

    Abstract: An untethered apparatus for performing inside-out device tracking based on visual-inertial simultaneous location and mapping (SLAM) includes a dynamic vision sensor (DVS) configured to output an asynchronous stream of sensor event data, an inertial measurement unit (IMU) sensor configured to collect IMU data associated with motion of the apparatus at a predetermined interval, a processor and a memory. The memory contains instructions, which when executed by the processor, cause the apparatus to accumulate DVS sensor output over a sliding time window, the sliding time window including the predetermined interval, apply a motion correction to the accumulated DVS sensor output, the motion correction based on the IMU data collected over the predetermined interval, generate an event-frame histogram of DVS sensor events based on the motion correction, and provide the event-frame histogram of the DVS sensor events and the IMU data to a visual inertial SLAM pipeline.

    Semantic mapping for low-power augmented reality using dynamic vision sensor

    公开(公告)号:US10812711B2

    公开(公告)日:2020-10-20

    申请号:US16415860

    申请日:2019-05-17

    Abstract: An apparatus includes a dynamic vision sensor (DVS) configured to output an asynchronous stream of sensor event data, a CMOS image sensor configured to output frames of image data, an inertial measurement unit (IMU), a processor and a memory. The memory contains instructions, which when executed by the processor, cause the apparatus to generate a semantic segmentation of a time-stamped frame, which is based on one or more of an output of the CMOS image sensor, or a synthesized event frame based on an output from the DVS and an output from the IMU over a time interval. The semantic segmentation includes a semantic label associated with a region of the time-stamped frame. When executed, the instructions further cause the apparatus to determine, based on the semantic segmentation, a simplified object representation in a coordinate space, and update a stable semantic map based on the simplified object representation.

    SEMANTIC MAPPING FOR LOW-POWER AUGMENTED REALITY USING DYNAMIC VISION SENSOR

    公开(公告)号:US20190355169A1

    公开(公告)日:2019-11-21

    申请号:US16415860

    申请日:2019-05-17

    Abstract: An apparatus includes a dynamic vision sensor (DVS) configured to output an asynchronous stream of sensor event data, a CMOS image sensor configured to output frames of image data, an inertial measurement unit (IMU), a processor and a memory. The memory contains instructions, which when executed by the processor, cause the apparatus to generate a semantic segmentation of a time-stamped frame, which is based on one or more of an output of the CMOS image sensor, or a synthesized event frame based on an output from the DVS and an output from the IMU over a time interval. The semantic segmentation includes a semantic label associated with a region of the time-stamped frame. When executed, the instructions further cause the apparatus to determine, based on the semantic segmentation, a simplified object representation in a coordinate space, and update a stable semantic map based on the simplified object representation.

    CMOS-ASSISTED INSIDE-OUT DYNAMIC VISION SENSOR TRACKING FOR LOW POWER MOBILE PLATFORMS

    公开(公告)号:US20210075964A1

    公开(公告)日:2021-03-11

    申请号:US16953111

    申请日:2020-11-19

    Abstract: An untethered apparatus for performing inside-out device tracking based on visual-inertial simultaneous location and mapping (SLAM) includes a dynamic vision sensor (DVS) configured to output an asynchronous stream of sensor event data, an inertial measurement unit (IMU) sensor configured to collect IMU data associated with motion of the apparatus at a predetermined interval, a processor and a memory. The memory contains instructions, which when executed by the processor, cause the apparatus to accumulate DVS sensor output over a sliding time window, the sliding time window including the predetermined interval, apply a motion correction to the accumulated DVS sensor output, the motion correction based on the IMU data collected over the predetermined interval, generate an event-frame histogram of DVS sensor events based on the motion correction, and provide the event-frame histogram of the DVS sensor events and the IMU data to a visual inertial SLAM pipeline.

    CAMERA POSE DETERMINATION AND TRACKING
    10.
    发明申请

    公开(公告)号:US20190096081A1

    公开(公告)日:2019-03-28

    申请号:US15962757

    申请日:2018-04-25

    Abstract: A system for determining and tracking camera pose includes a dynamic vision sensor (DVS) configured to generate a current DVS image, an inertial measurement unit (IMU) configured to generate inertial data, and a memory. The memory is configured to store a 3-dimensional (3D) map of a known 3D environment. The system may also include a processor coupled to the memory. The processor is configured to initiate operations including determining a current camera pose for the DVS based on the current DVS image, the inertial data, the 3D map, and a prior camera pose.

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