Abstract: This application discloses a photographing apparatus and method, and relates to the field of image processing. When a high-quality image in a low illumination environment is obtained, costs are reduced, a size is reduced, and product compatibility is improved. The method includes: controlling a light filtering unit to: transparently transmit visible light in incident light and block infrared light in the incident light in a first image exposure interval, transparently transmit the infrared light in the incident light in a first time period of a second image exposure interval, and block the incident light in a second time period of the second image exposure interval; performing, by using an image sensor to obtain a first image, and performing photoelectric imaging on a light ray to obtain a second image; and synthesizing the first image and the second image, to generate a first target image.

Abstract: Embodiments of the present application relate to the technical field of robot control, and in particular, to an unmanned aerial vehicle (UAV) path planning method and apparatus and a UAV. The UAV path planning method includes: acquiring a depth map of an environment in front of a UAV; acquiring a grid map centered on a body of the UAV according to the depth map; determining candidate flight directions for the UAV according to the grid map; determining an optimal flight direction for the UAV from the candidate flight directions; and controlling the UAV to fly in the optimal flight direction to avoid an obstacle in the environment in front of the UAV. In this way, the embodiments of the present application can accurately determine an obstacle that suddenly appears in an unknown environment and a dynamic environment, so as to achieve real-time path planning.

Abstract: An optical fiber alignment system is disclosed. The alignment system includes a reflective mirror, an image capturing system, and a data processing system. The reflective mirror is configured to simultaneously reflect a first illuminated image of a first optical fiber and a second illuminated image of a second optical fiber. The image capturing system is configured to receive the reflected first and second illuminated images and to convert the first and second illuminated images into computer-readable image data. The data processing system is configured to receive the image data from the image capturing system and to control movement of at least one of the first optical fiber and the second optical fiber based upon the image data.

Abstract: The present invention relates to a method and device for estimating a distance to a target, and a unmanned aerial vehicle. The method is applicable to a unmanned aerial vehicle including a photographing device. The method includes: acquiring a current frame of image of the target captured by the photographing device; acquiring location information of the target according to the current frame of image, where the location information includes a height of the target and two-dimensional pixel coordinates of the target in the image; acquiring attitude information of the photographing device, where the attitude information includes a pitch angle of the photographing device; and acquiring a distance between the target and the unmanned aerial vehicle according to the location information of the target and the attitude information of the photographing device.

Abstract: A position estimation method for a tracking target is implemented in an unmanned aerial vehicle. The position estimation method include: estimating a target position of the tracking target at the next time according to an initial position of the tracking target at the current moment; determining an estimated width and an estimated height of the tracking target in an image captured by a pan-tilt-zoom camera of the unmanned aerial vehicle according to the estimated target position; obtaining an actual width and an actual height of the tracking target in the image; determining a height difference between the estimated width and the estimated height and a width difference between the actual height and the actual width; and updating the target position of the tracking target at the next time according to the height difference and the width difference.

Abstract: The present disclosure relates to methods of assembling a lensed optical fiber array by printing in situ a lens onto each optical fiber of an optical fiber array with an ultrafast laser system where the lens can be shaped to the optical fiber end face to reduce pitch mismatch. In some embodiments, optical fiber(s) of the optical fiber array can be cleaved, and the lens can be shaped to the optical fiber end face to reduce pitch mismatch.

Abstract: This application discloses a photographing apparatus and method, and relates to the field of image processing. When a high-quality image in a low illumination environment is obtained, costs are reduced, a size is reduced, and product compatibility is improved. The method includes: controlling a light filtering unit to: transparently transmit visible light in incident light and block infrared light in the incident light in a first image exposure interval, transparently transmit the infrared light in the incident light in a first time period of a second image exposure interval, and block the incident light in a second time period of the second image exposure interval; performing, by using an image sensor to obtain a first image, and performing photoelectric imaging on a light ray to obtain a second image; and synthesizing the first image and the second image, to generate a first target image.

Abstract: Systems and methods for assessing multi-layer structures in which a spectrum array is generated from low coherence interferometry and input into a statistical estimator, which determines the thickness and layer number based on the inputted spectrum and other information, including information about a source intensity noise, Poisson noise, and dark noise associated with the low coherence interferometry.

Abstract: The method includes: obtaining a target image acquired by the camera apparatus, and performing image recognition on the target image, to obtain a target image region of a target in the target image; obtaining a raw point cloud of a surrounding environment of the UAV, and obtaining a first target location according to the target image region and the raw point cloud; obtaining attitude information of the camera apparatus, obtaining a first image location based on the target image region, and obtaining a second target location according to the first image location and the attitude information; obtaining a second image location based on the target image region; initializing a target state according to the first target location or the second target location; and using the first target location and/or the second target location and/or the second image location as measured values of an extended Kalman filter to obtain the target state.

Abstract: Non-contact methods of predicting an insertion loss of a test optical fiber connector are disclosed. Light is sent down the at least one optical fiber of the connector in the fundamental mode to emit an output light beam. The output-beam image is captured at different distances from the fiber end faces to define multiple output-beam images each associated with one of the multiple measurement positions. A Gaussian curve is then fitted to the multiple output-beam images to determine a mode field diameter, an offset, and a tilt of the output light beam. A Gaussian field model that incorporates the offset, the tilt, and the mode-field diameter is then used to predict the insertion loss when connecting to a reference optical fiber of a reference optical fiber connector.

Abstract: The present invention relates to a method and device for estimating a distance to a target, and a unmanned aerial vehicle. The method is applicable to a unmanned aerial vehicle including a photographing device. The method includes: acquiring a current frame of image of the target captured by the photographing device; acquiring location information of the target according to the current frame of image, where the location information includes a height of the target and two-dimensional pixel coordinates of the target in the image; acquiring attitude information of the photographing device, where the attitude information includes a pitch angle of the photographing device; and acquiring a distance between the target and the unmanned aerial vehicle according to the location information of the target and the attitude information of the photographing device.

Abstract: Embodiments of the present application relate to the technical field of robot control, and in particular, to an unmanned aerial vehicle (UAV) path planning method and apparatus and a UAV. The UAV path planning method includes: acquiring a depth map of an environment in front of a UAV; acquiring a grid map centered on a body of the UAV according to the depth map; determining candidate flight directions for the UAV according to the grid map; determining an optimal flight direction for the UAV from the candidate flight directions; and controlling the UAV to fly in the optimal flight direction to avoid an obstacle in the environment in front of the UAV. In this way, the embodiments of the present application can accurately determine an obstacle that suddenly appears in an unknown environment and a dynamic environment, so as to achieve real-time path planning.

Abstract: Non-contact methods of predicting an insertion loss of a test optical fiber connector are disclosed. Light is sent down the at least one optical fiber of the connector in the fundamental mode to emit an output light beam. The output-beam image is captured at different distances from the fiber end faces to define multiple output-beam images each associated with one of the multiple measurement positions. A Gaussian curve is then fitted to the multiple output-beam images to determine a mode field diameter, an offset, and a tilt of the output light beam. A Gaussian field model that incorporates the offset, the tilt, and the mode-field diameter is then used to predict the insertion loss when connecting to a reference optical fiber of a reference optical fiber connector.

Abstract: Systems and methods for assessing multi-layer structures in which a spectrum array is generated from low coherence interferometry and input into a statistical estimator, which determines the thickness and layer number based on the inputted spectrum and other information, including information about a source intensity noise, Poisson noise, and dark noise associated with the low coherence interferometry.

Abstract: Systems and methods for determining thickness of lipid and aqueous layers of a tear film in which a spectrum array is generated from optical coherence tomography and input into a statistical estimator, which determines the thickness of the lipid and/or aqueous layers at a nanometer resolution based on the inputted spectrum and other information, such as information about a laser intensity noise, Poisson noise, and dark noise associated with the OCT.

Abstract: Systems and methods for determining thickness of lipid and aqueous layers of a tear film in which a spectrum array is generated from optical coherence tomography and input into a statistical estimator, which determines the thickness of the lipid and/or aqueous layers at a nanometer resolution based on the inputted spectrum and other information, such as information about a laser intensity noise, Poisson noise, and dark noise associated with the OCT.

Abstract: Systems and methods for determining thickness of lipid and aqueous layers of a tear film in which a spectrum array is generated from optical coherence tomography and input into a statistical estimator, which determines the thickness of the lipid and/or aqueous layers at a nanometer resolution based on the inputted spectrum and other information, such as information about a laser intensity noise, Poisson noise, and dark noise associated with the OCT.