Abstract: A neural network may be used to determine corner points of a skewed polygon (e.g., as displacement values to anchor box corner points) that accurately delineate a region in an image that defines a parking space. Further, the neural network may output confidence values predicting likelihoods that corner points of an anchor box correspond to an entrance to the parking spot. The confidence values may be used to select a subset of the corner points of the anchor box and/or skewed polygon in order to define the entrance to the parking spot. A minimum aggregate distance between corner points of a skewed polygon predicted using the CNN(s) and ground truth corner points of a parking spot may be used simplify a determination as to whether an anchor box should be used as a positive sample for training.

Abstract: In various examples, one or more deep neural networks (DNNs) are executed to regress on control points of a curve, and the control points may be used to perform a curve fitting operation—e.g., Bezier curve fitting—to identify landmark locations and geometries in an environment. The outputs of the DNN(s) may thus indicate the two-dimensional (2D) image-space and/or three-dimensional (3D) world-space control point locations, and post-processing techniques—such as clustering and temporal smoothing—may be executed to determine landmark locations and poses with precision and in real-time. As a result, reconstructed curves corresponding to the landmarks—e.g., lane line, road boundary line, crosswalk, pole, text, etc.—may be used by a vehicle to perform one or more operations for navigating an environment.

Abstract: A neural network may be used to determine corner points of a skewed polygon (e.g., as displacement values to anchor box corner points) that accurately delineate a region in an image that defines a parking space. Further, the neural network may output confidence values predicting likelihoods that corner points of an anchor box correspond to an entrance to the parking spot. The confidence values may be used to select a subset of the corner points of the anchor box and/or skewed polygon in order to define the entrance to the parking spot. A minimum aggregate distance between corner points of a skewed polygon predicted using the CNN(s) and ground truth corner points of a parking spot may be used simplify a determination as to whether an anchor box should be used as a positive sample for training.

Abstract: In various examples, a path perception ensemble is used to produce a more accurate and reliable understanding of a driving surface and/or a path there through. For example, an analysis of a plurality of path perception inputs provides testability and reliability for accurate and redundant lane mapping and/or path planning in real-time or near real-time. By incorporating a plurality of separate path perception computations, a means of metricizing path perception correctness, quality, and reliability is provided by analyzing whether and how much the individual path perception signals agree or disagree. By implementing this approach—where individual path perception inputs fail in almost independent ways—a system failure is less statistically likely. In addition, with diversity and redundancy in path perception, comfortable lane keeping on high curvature roads, under severe road conditions, and/or at complex intersections, as well as autonomous negotiation of turns at intersections, may be enabled.

Abstract: In various examples, a deep neural network (DNN) is trained for sensor blindness detection using a region and context-based approach. Using sensor data, the DNN may compute locations of blindness or compromised visibility regions as well as associated blindness classifications and/or blindness attributes associated therewith. In addition, the DNN may predict a usability of each instance of the sensor data for performing one or more operations—such as operations associated with semi-autonomous or autonomous driving. The combination of the outputs of the DNN may be used to filter out instances of the sensor data—or to filter out portions of instances of the sensor data determined to be compromised—that may lead to inaccurate or ineffective results for the one or more operations of the system.

Abstract: In various examples, systems and methods are disclosed that preserve rich spatial information from an input resolution of a machine learning model to regress on lines in an input image. The machine learning model may be trained to predict, in deployment, distances for each pixel of the input image at an input resolution to a line pixel determined to correspond to a line in the input image. The machine learning model may further be trained to predict angles and label classes of the line. An embedding algorithm may be used to train the machine learning model to predict clusters of line pixels that each correspond to a respective line in the input image. In deployment, the predictions of the machine learning model may be used as an aid for understanding the surrounding environment—e.g., for updating a world model—in a variety of autonomous machine applications.

Abstract: Example methods, systems, computer-readable media, and apparatuses for on-screen optical fingerprint capture for user authentication are presented. These allow for the authentication of a fingerprint where the fingerprint image is propagated in a glass layer before being captured by a camera. In some examples, such propagation can result in multiple fingerprint images resulting from total internal reflection within the glass layer. Feature information can then be determined from the captured image of the fingerprint, which can include multiple fingerprint images. The amount of feature information can then be reduced. A histogram associated with the captured image based on the reduced number of features can be generated, and a user can be authenticated based on the histogram.

Abstract: An apparatus includes a hardware sensor array including a plurality of pixels arranged along at least a first dimension and a second dimension of the array, each of the pixels capable of generating a sensor reading. A hardware scanning window array includes a plurality of storage elements arranged along at least a first dimension and a second dimension of the hardware scanning window array, each of the storage elements capable of storing a pixel value based on one or more sensor readings. Peripheral circuitry for systematically transfers pixel values, based on sensor readings, into the hardware scanning window array, to cause different windows of pixel values to be stored in the hardware scanning window array at different times. Control logic coupled to the hardware sensor array, the hardware scanning window array, and the peripheral circuitry, provides control signals to the peripheral circuitry to control the transfer of pixel values.

Abstract: Methods, systems, computer-readable media, and apparatuses for biometric imaging are presented. The biometric imaging can include emitting light, using a light emitter, wherein the emitted light passes through a display comprising quantum dots. The quantum dots can be configured to emit non-visible light. The biometric imaging can further include sensing, using a sensor, the non-visible light emitted from the quantum dots and reflected from an object to be imaged.

Abstract: Example methods, systems, computer-readable media, and apparatuses for on-screen optical fingerprint capture for user authentication are presented. These allow for the authentication of a fingerprint where the fingerprint image is propagated in a glass layer before being captured by a camera. In some examples, such propagation can result in multiple fingerprint images resulting from total internal reflection within the glass layer. Feature information can then be determined from the captured image of the fingerprint, which can include multiple fingerprint images. The amount of feature information can then be reduced. A histogram associated with the captured image based on the reduced number of features can be generated, and a user can be authenticated based on the histogram.

Abstract: This disclosure provides systems, methods and apparatus for touch and gesture recognition, using a field sequential color display. The display includes a processor, a lighting system, and an arrangement for spatial light modulation that includes an array of light modulators. Each light modulator is switchable between an open position that permits transmittance of light from the lighting system through a respective aperture and a shut position that blocks light transmission through the respective aperture. The processor switches the light modulators in accordance with a first modulation scheme to render an image and in accordance with a second modulation scheme to selectively pass object illuminating light through at least one of the respective apertures. A light sensor receives light resulting from interaction of the object illuminating with an object and outputs a signal to the processor. The processor recognizes, from the output of the light sensor, a characteristic of the object.

Abstract: An apparatus includes a hardware sensor array including a plurality of pixels arranged along at least a first dimension and a second dimension of the array, each of the pixels capable of generating a sensor reading. A hardware scanning window array includes a plurality of storage elements arranged along at least a first dimension and a second dimension of the hardware scanning window array, each of the storage elements capable of storing a pixel value based on one or more sensor readings. Peripheral circuitry for systematically transfers pixel values, based on sensor readings, into the hardware scanning window array, to cause different windows of pixel values to be stored in the hardware scanning window array at different times. Control logic coupled to the hardware sensor array, the hardware scanning window array, and the peripheral circuitry, provides control signals to the peripheral circuitry to control the transfer of pixel values.

Abstract: A system for image processing that matches a model image with an input image. The matching process includes using a feature location index for the model image.

Abstract: Systems, methods, and apparatus for recognizing user interactions with an electronic device are provided. Implementations of the systems, methods, and apparatus include surface and air gesture recognition and identification of fingertips or other objects. In some implementations, a device including a plurality of detectors configured to receive signals indicating interaction of an object with the device at or above a detection area, such that a low resolution image can be generated from the signals, is provided. The device is configured to obtain low resolution image data from the signals and obtain a first reconstructed depth map from the low resolution image data. The first reconstructed depth map may have a higher resolution than the low resolution image. The device is further configured to obtain a second reconstructed depth map from the first reconstructed depth map. The second reconstructed depth map may provide improved boundaries and less noise within the object.

Abstract: A system for enhancing an input image including receiving an input image and filtering the input image with a plurality of non-linear smoothing filters providing a respective plurality of filtered outputs. The system processes a plurality of the filtered outputs with respect to at least one of another of the filtered outputs and the input image to determine a plurality of detail layers. The system filters the plurality of detail layers with a plurality of non-linear smoothing filters providing a respective plurality of smoothed layers. The system adjusts the plurality of smoothed layers in such a manner that regions closer to an edge are enhanced to a lesser extent than regions farther from an edge and combining the adjusted the smoothed layers to provide an enhanced output image.

Abstract: A system for enhancing an input image including receiving an input image and filtering the input image with a plurality of non-linear smoothing filters providing a respective plurality of filtered outputs. The system processes a plurality of the filtered outputs with respect to at least one of another of the filtered outputs and the input image to determine a plurality of detail layers. The system filters the plurality of detail layers with a plurality of non-linear smoothing filters providing a respective plurality of smoothed layers. The system adjusts the plurality of smoothed layers in such a manner that regions closer to an edge are enhanced to a lesser extent than regions farther from an edge and combining the adjusted the smoothed layers to provide an enhanced output image.

Abstract: This disclosure provides systems, methods and apparatus for touch and gesture recognition, using a field sequential color display. The display includes a processor, a lighting system, and an arrangement for spatial light modulation that includes an array of light modulators. Each light modulator is switchable between an open position that permits transmittance of light from the lighting system through a respective aperture and a shut position that blocks light transmission through the respective aperture. The processor switches the light modulators in accordance with a first modulation scheme to render an image and in accordance with a second modulation scheme to selectively pass object illuminating light through at least one of the respective apertures. A light sensor receives light resulting from interaction of the object illuminating with an object and outputs a signal to the processor. The processor recognizes, from the output of the light sensor, a characteristic of the object.

Abstract: This disclosure provides systems, methods and apparatus for touch and gesture recognition, using a field sequential color display. The display includes a processor, a lighting system, and an arrangement for spatial light modulation that includes an array of light modulators. Each light modulator is switchable between an open position that permits transmittance of light from the lighting system through a respective aperture and a shut position that blocks light transmission through the respective aperture. The processor switches the light modulators in accordance with a first modulation scheme to render an image and in accordance with a second modulation scheme to selectively pass object illuminating light through at least one of the respective apertures. A light sensor receives light resulting from interaction of the object illuminating with an object and outputs a signal to the processor. The processor recognizes, from the output of the light sensor, a characteristic of the object.

Abstract: This disclosure provides systems, methods and apparatus for touch and gesture recognition, using a field sequential color display. The display includes a processor, a lighting system, and an arrangement for spatial light modulation that includes a number of apertures, and devices for opening and shutting the apertures. A light directing arrangement includes at least one light turning feature. The display lighting system is configured to emit visible light and infrared (IR) light through at least a first opened one of the plurality of apertures. The light turning feature is configured to redirect IR light emitted through the opened aperture into at least one lobe, and to pass visible light emitted by the display lighting system through the opened aperture with substantially no redirection.

Abstract: This disclosure provides systems, methods and apparatus for touch and gesture recognition, using a field sequential color display. The display includes a processor, a lighting system, and an arrangement for spatial light modulation that includes an array of light modulators. Each light modulator is switchable between an open position that permits transmittance of light from the lighting system through a respective aperture and a shut position that blocks light transmission through the respective aperture. The processor switches the light modulators in accordance with a first modulation scheme to render an image and in accordance with a second modulation scheme to selectively pass object illuminating light through at least one of the respective apertures. A light sensor receives light resulting from interaction of the object illuminating with an object and outputs a signal to the processor. The processor recognizes, from the output of the light sensor, a characteristic of the object.