Abstract: Disclosed is a system for controlling a robot via a foot-operable controller. The foot-operable controller includes a grid of large pressure-sensitive tiles that are responsive to being stepped on. Signals from the pressure-sensitive tiles are provided to a controller interface that converts the signals to control messages compatible with existing robot control interfaces, such as a universal serial bus. The foot-operable controller may be used to control various robots, including for example a robot equipped with a claw arm or a robot equipped with a ring launcher.

Abstract: Apparatus and methods are disclosed for a standalone and multi-game miniature golf structure. A sensor assembly located at an end of a putting surface of a putting structure includes a panel and a sensor. The panel is positioned adjacent to and below the end of the putting surface. The panel defines an upper surface along which a golf ball is to travel after dropping from the end of the putting surface. The upper surface includes a rear edge and a front edge. The sensor is positioned adjacent the panel to detect at which of a plurality of lateral positions the golf ball travels along the upper surface.

Abstract: A non-transitory computer-readable storage medium stores executable instructions that, when executed by a processor, cause performance of operations comprising operations to access an image captured by an image sensor, obtain a transfer function for mapping pixel values, determine a faces indication that reflects a proportion of a scene depicted in the image that includes one or more human faces, and modify the transfer function based on the faces indication. Modifying the transfer function based on the faces indication comprises adjusting a gain of the transfer function to move the gain closer to unity. The operations include to apply the transfer function to pixel values of the image to produce a tone mapped image and output the tone mapped image.

Abstract: A camera mode to use for capturing an image or video is selected by estimating high dynamic range (HDR), motion, and light intensity with respect to a scene of the image or video to capture. An image capture device includes a HDR estimation unit to detect whether HDR is present in a scene of an image to capture, a motion estimation unit to determine whether motion is detected within the scene, and a light intensity estimation unit to determine whether a scene luminance for the scene meets a threshold. A mode selection unit selects a camera mode to use for capturing the image based on output of the HDR estimation unit, the motion estimation unit, and the light intensity estimation unit. An image sensor captures the image according to the selected camera mode.

Abstract: An image capture device includes an image sensor and a processor. The image sensor is configured to capture a first plurality of frames, a second plurality of frames, and a third plurality of frames. The processor includes a first denoising layer and a second denoising layer. The first denoising layer includes a first denoiser, a second denoiser, and a third denoiser. The first denoiser is configured to denoise the first plurality of frames and output a first denoised frame. The second denoiser is configured to denoise the second plurality of frames and output a second denoised frame. The third denoiser is configured to denoise the third plurality of frames and output a third denoised frame. The second denoising layer includes a fourth denoiser. The fourth denoiser is configured to output a denoised frame based on the first denoised frame, the second denoised frame, and the third denoised frame.

Abstract: A non-transitory computer-readable storage medium stores executable instructions that, when executed by a processor, cause performance of operations comprising operations to access an image captured by an image sensor, obtain a transfer function for mapping pixel values, determine a faces indication that reflects a proportion of a scene depicted in the image that includes one or more human faces, and modify the transfer function based on the faces indication. Modifying the transfer function based on the faces indication comprises adjusting a gain of the transfer function to move the gain closer to unity. The operations include to apply the transfer function to pixel values of the image to produce a tone mapped image and output the tone mapped image.

Abstract: The invention relates to polymorphous crystal modifications of a DPP-IV inhibitor, the preparation thereof and the use thereof for preparing a medicament.

Abstract: An image capture device includes an image sensor and a processor. The image sensor is configured to capture a first plurality of frames, a second plurality of frames, and a third plurality of frames. The processor includes a first denoising layer and a second denoising layer. The first denoising layer includes a first denoiser, a second denoiser, and a third denoiser. The first denoiser is configured to denoise the first plurality of frames and output a first denoised frame. The second denoiser is configured to denoise the second plurality of frames and output a second denoised frame. The third denoiser is configured to denoise the third plurality of frames and output a third denoised frame. The second denoising layer includes a fourth denoiser. The fourth denoiser is configured to output a denoised frame based on the first denoised frame, the second denoised frame, and the third denoised frame.

Abstract: Systems and methods are disclosed for image signal processing. For example, methods may include receiving an image from an image sensor; applying a filter to the image to obtain a low-frequency component image and a high-frequency component image; determining a first enhanced image based on a weighted sum of the low-frequency component image and the high-frequency component image, where the high-frequency component image is weighted more than the low-frequency component image; determining a second enhanced image based on the first enhanced image and a tone mapping; and storing, displaying, or transmitting an output image based on the second enhanced image.

Abstract: A camera mode to use for capturing an image or video is selected by estimating high dynamic range (HDR), motion, and light intensity with respect to a scene of the image or video to capture. An image capture device includes a HDR estimation unit to detect whether HDR is present in a scene of an image to capture, a motion estimation unit to determine whether motion is detected within the scene, and a light intensity estimation unit to determine whether a scene luminance for the scene meets a threshold. A mode selection unit selects a camera mode to use for capturing the image based on output of the HDR estimation unit, the motion estimation unit, and the light intensity estimation unit. An image sensor captures the image according to the selected camera mode.

Abstract: A system accesses an image with each pixel of the image having luminance values each representative of a color component of the pixel. The system generates a first histogram for aggregate luminance values of the image, and accesses a target histogram for the image representative of a desired global image contrast. The system computes a transfer function based on the first histogram and the target histogram such that when the transfer function is applied, a histogram of the modified aggregate luminance values is within a threshold similarity of the target histogram. The system modifies the image by applying the transfer function to the luminance values of the image to produce a tone mapped image, and outputs the modified image.

Abstract: Systems and methods are disclosed for denoising chrominance channels of images. For example, methods may include receiving an image from one or more image sensors; determining a set of weights for the image based on a luminance channel of the image, wherein a weight in the set of weights corresponds to a subject pixel and a candidate pixel and is determined based on luminance values of one or more pixels of the image centered at the subject pixel and one or more pixels of the image centered at the candidate pixel; applying the set of weights to chrominance channels of the image to obtain a denoised image, wherein the subject pixel of the denoised image is determined based on the weight multiplied by the candidate pixel of the image; and storing, displaying, or transmitting an output image based on the denoised image.

Abstract: Systems and methods are disclosed for image signal processing. For example, methods may include receiving an image from an image sensor; applying a filter to the image to obtain a low-frequency component image and a high-frequency component image; determining a first enhanced image based on a weighted sum of the low-frequency component image and the high-frequency component image, where the high-frequency component image is weighted more than the low-frequency component image; determining a second enhanced image based on the first enhanced image and a tone mapping; and storing, displaying, or transmitting an output image based on the second enhanced image.

Abstract: A camera mode to use for capturing an image or video is selected by estimating high dynamic range (HDR), motion, and light intensity with respect to a scene of the image or video to capture. An image capture device includes a HDR estimation unit to detect whether HDR is present in a scene of an image to capture, a motion estimation unit to determine whether motion is detected within the scene, and a light intensity estimation unit to determine whether a scene luminance for the scene meets a threshold. A mode selection unit selects a camera mode to use for capturing the image based on output of the HDR estimation unit, the motion estimation unit, and the light intensity estimation unit. An image sensor captures the image according to the selected camera mode.

Abstract: Systems and methods are disclosed for image signal processing. For example, methods may include receiving a current image of a sequence of images from an image sensor; combining the current image with a recirculated image to obtain a noise reduced image, where the recirculated image is based on one or more previous images of the sequence of images from the image sensor; determining a noise map for the noise reduced image, where the noise map is determined based on estimates of noise levels for pixels in the current image, a noise map for the recirculated image, and a set of mixing weights; recirculating the noise map with the noise reduced image to combine the noise reduced image with a next image of the sequence of images from the image sensor; and storing, displaying, or transmitting an output image that is based on the noise reduced image.

Abstract: A method for deblurring a target image includes receiving a burst of images that includes the target image; partitioning respective images of the burst of images into respective patches; converting, to a frequency domain, the respective patches into respective transform patches; selecting a first set of corresponding transform patches from the respective transform patches, where the first set of the corresponding transform patches includes a respective transform patch for a respective image of the burst of images; obtaining, using a neural network, respective weight maps for the corresponding transform patches; obtaining a deblurred transform patch by combining the first set of corresponding transform patches using the respective weight maps; obtaining a first deblurred patch by converting the deblurred transform patch to a pixel domain; and obtaining a deblurred image of the target image using the first deblurred patch.

Abstract: Systems and methods are disclosed for image signal processing. For example, methods may include receiving a current image of a sequence of images from an image sensor; combining the current image with a recirculated image to obtain a noise reduced image, where the recirculated image is based on one or more previous images of the sequence of images from the image sensor; determining a noise map for the noise reduced image, where the noise map is determined based on estimates of noise levels for pixels in the current image, a noise map for the recirculated image, and a set of mixing weights; recirculating the noise map with the noise reduced image to combine the noise reduced image with a next image of the sequence of images from the image sensor; and storing, displaying, or transmitting an output image that is based on the noise reduced image.

Abstract: An image capture apparatus may include an image sensor, a motion sensor, and an auto-exposure unit. The auto-exposure unit may obtain an input image captured during an exposure interval and corresponding motion data indicating motion of the image capture apparatus during the exposure interval. The auto-exposure unit may obtain image information-amount data for the input image. The auto-exposure unit may obtain derivative information-amount data based on the information-amount data and a candidate exposure adjustment. The auto-exposure unit may obtain an information-amount maximizing exposure interval based on the information-amount data and the derivative information-amount data. The image capture apparats may control the image sensor to obtain a subsequent input image signal representing a subsequent input image captured during the information-amount maximizing exposure interval, and output or store information representing the subsequent input image.

Abstract: Systems and methods are disclosed for image signal processing. For example, methods may include accessing an image from an image sensor; detecting an object area on the image; classifying the object area on the image; applying a filter to an object area of the image to obtain a low-frequency component image and a high-frequency component image; determining a first enhanced image based on a weighted sum of the low-frequency component image and the high-frequency component image, where the high-frequency component image is weighted more than the low-frequency component image; determining a second enhanced image based on the first enhanced image and a tone mapping; and storing, displaying, or transmitting an output image based on the second enhanced image.

Abstract: A camera mode to use for capturing an image or video is selected by estimating high dynamic range (HDR), motion, and light intensity with respect to a scene of the image or video to capture. An image capture device includes a HDR estimation unit to detect whether HDR is present in a scene of an image to capture, a motion estimation unit to determine whether motion is detected within the scene, and a light intensity estimation unit to determine whether a scene luminance for the scene meets a threshold. A mode selection unit selects a camera mode to use for capturing the image based on output of the HDR estimation unit, the motion estimation unit, and the light intensity estimation unit. An image sensor captures the image according to the selected camera mode.