Abstract: Digital ink is generated to represent a visual component, such as a letter, number, character, and/or other symbol. The digital ink is generated by obtaining multiple different curves that combine to generate the visual component. These different curves can have various different characteristics (e.g., different thicknesses) to provide the desired visual component. The combined curves are converted into a set of primitives that make up the parts of the combined curves, and the set of primitives are converted into a digital ink format. Data describing the set of primitives in digital ink format can be stored and subsequently used to display the visual component as digital ink.

Abstract: In aspects of replay of recorded touch input data, a computing device can store recorded touch input data that has been previously recorded based on multiple instances of user inadvertent contact on touch-enabled devices. A replay test application is implemented to test one or more user devices for inadvertent contact rejection using the recorded touch input data, such as to test a palm rejection algorithm of a user device. The replay test application is implemented to communicate the recorded touch input data to a screen overlay device that generates touch inputs on a touchscreen of the user device to test the palm rejection algorithm of the user device. The replay test application also monitors the user device for an action responsive to a touch input that is not filtered as an inadvertent contact with the touchscreen of the user device.

Abstract: A computing device includes a digital input system that provides digital input functionality for the computing device. The digital input system receives both a first input and a second input. The first input is typically an input with the user's dominant hand (e.g., using a pen, stylus, finger, etc.), and the second input is typically an input with the user's non-dominant hand. The digital input system determines whether a second input is received simultaneously with the first input, and selects one of multiple behaviors for the first input based on whether the second input is received simultaneously with the first input. Various different behaviors for the first input can be selected from, such as freehand or freeform input, constraining digital input corresponding to the first input to be along an edge of a stencil, and so forth.

Abstract: A computing system includes a capacitive touch-display including a plurality of touch-sensing pixels, a digitizer configured to generate one or more capacitive grid maps, and an operating system. Each capacitive grid map includes a capacitance value for each of the plurality of touch-sensing pixels. The controller may be configured to receive the one or more capacitive grid maps directly from the digitizer, identify one or more touch inputs based on the one or more capacitive grid maps, and determine a dominant hand of a user based on the one or more touch inputs.

Abstract: The techniques described herein implement a classification process to evaluate information associated with a tool input (e.g., from an input tool such as a pen or a stylus) and a user touch input (e.g., from a finger or a palm of a hand) to determine whether the user touch input is an intended or an unintended touch input. The information evaluated may be associated with an arrival of the tool input relative to an arrival of the user touch input. The information evaluated may also be associated with a movement of the tool input relative to a movement of the user touch input. In various implementations, the techniques may calculate an evaluation score and compare the evaluation score to a confidence classification threshold. If a confident classification cannot be achieved, the techniques further the classification process as more information associated with the inputs is received.

Abstract: A computing system includes a capacitive touch-display including a plurality of touch-sensing pixels, a digitizer configured to generate a capacitive grid map including a capacitance value for each of the plurality of touch-sensing pixels, and an operating system configured to receive the capacitive grid map directly from the digitizer.

Abstract: The techniques described herein implement a classification process to evaluate information associated with a tool input (e.g., from an input tool such as a pen or a stylus) and a user touch input (e.g., from a finger or a palm of a hand) to determine whether the user touch input is an intended or an unintended touch input. The information evaluated may be associated with an arrival of the tool input relative to an arrival of the user touch input. The information evaluated may also be associated with a movement of the tool input relative to a movement of the user touch input. In various implementations, the techniques may calculate an evaluation score and compare the evaluation score to a confidence classification threshold. If a confident classification cannot be achieved, the techniques further the classification process as more information associated with the inputs is received.

Abstract: A computing device including a capacitive touch screen and a processor configured to receive a capacitive image from the capacitive touch screen, determine that the capacitive image includes an image of a capacitive tag, identify a pattern of capacitive elements of the capacitive tag based on the capacitive image, determine bits of encoded data based on the identified pattern of capacitive elements, and process the encoded data.

Abstract: Techniques and architectures for detecting the handedness of a user from touch input and suppressing unintentional touch input are described. The techniques and architectures may analyze short-lived contacts that occur on a touch surface around a same time as input from an input tool to determine a hand that a user is using to hold the input tool. An inactive region may be established for the touch surface based on the hand determination and/or contextual information related to the user, the touch surface and so on. The inactive region may allow unintentional input to be identified and suppressed.

Abstract: A computing device includes a digital input system that provides digital input functionality for the computing device. The digital input system receives both a first input and a second input. The first input is typically an input with the user's dominant hand (e.g., using a pen, stylus, finger, etc.), and the second input is typically an input with the user's non-dominant hand. The digital input system determines whether a second input is received simultaneously with the first input, and selects one of multiple behaviors for the first input based on whether the second input is received simultaneously with the first input. Various different behaviors for the first input can be selected from, such as freehand or freeform input, constraining digital input corresponding to the first input to be along an edge of a stencil, and so forth.

Abstract: A computing device includes a digital input system that allows freehand digital inputs to be received (e.g., via movement of a pen, stylus, finger, etc.). The digital input system provides functionality allowing applications to receive digital inputs from a user and control the display of data based on the digital inputs. The digital input system receives digital input from a user and analyzes the digital input to collect input data for the digital input. As the digital input is received, the input data is made available to an application, allowing the application to operate on the input data (e.g., modify the input data and/or generate additional input data) and provide the operated-on input data to the digital input system. The digital input system then proceeds to control the display of data based on the operated-on input data.

Abstract: Systems, methods, and computer-readable storage media are provided for efficient real-time ink stroke smoothing, trajectory prediction, and GPU-leveraged rendering of ink stroke input. First and second ink points are received and an active Bézier approximation is computed based thereupon. Sequentially later in time that the first and second ink points, a third ink point is received. It is determined whether the third ink point adequately fits the active Bézier approximation. Where it is determined that the third ink point adequately fits, an updated active Bézier approximation is computed that includes the first, second and third ink points. Where it is determined that the third ink point fails to adequately fit, a different new Bézier approximation is computed that includes the third ink point but not the first and second ink points. Leveraging a GPU, a smoothed ink stroke based upon the Bézier approximation(s) is rendered.

Abstract: The techniques described herein are directed to receiving parameters directed to correcting spatial error and/or jitter associated with an interaction device connected to a computing device. In some instances, the parameters are encrypted parameters that may be decrypted and consumed to correct the spatial error and/or the jitter associated with the interaction device. For instance, the parameters may provide an adjustment to one or more reported positions of input received from a detection area of the interaction device, so that a display position more accurately reflects, based on the adjustment, an actual position of input on the detection area of the interaction device.

Abstract: Techniques and architectures for detecting the handedness of a user from touch input and suppressing unintentional touch input are described. The techniques and architectures may analyze short-lived contacts that occur on a touch surface around a same time as input from an input tool to determine a hand that a user is using to hold the input tool. An inactive region may be established for the touch surface based on the hand determination and/or contextual information related to the user, the touch surface and so on. The inactive region may allow unintentional input to be identified and suppressed.

Abstract: Some embodiments of the invention are directed to techniques for determining whether a process on a computer system that is sending or receiving data, or is attempting to send or receive data, with another computer system is executing in kernel mode or user mode and providing an indicator of this determination to a security engine. In some embodiments, such an indication is provided to a security engine (e.g., a firewall) that implements a security policy based at least in part on whether the sending or receiving process is in kernel mode or user mode, and filter communications based on a process' operating mode. This enables a security engine to maintain security policies of greater specificity and thus improve security of a computer system.

Abstract: A computing environment in which devices interoperate with a plurality of hardware components. Inconsistencies in user experience when operating devices that may use different components are avoided by generating a signature for the components. The signature may be computed as a function of a first key and one or more parameter values obtainable from the component. The signature and parameter values may be stored in the component's memory, and may be obtainable while the component is in operation as part of the computing device. The device may validate the component by performing at least one function based on the signature, the one or more parameter values obtainable from the component, and a second key, which may or may not be identical to the first key. The device may change its interaction with the component, depending on whether the component was successfully validated.

Abstract: Described is a technology by which a transient storage device or secure execution environment-based (e.g., including an embedded processor) device validates a host computer system. The device compares hashes of host system data against valid hashes maintained in protected storage of the device. The host data may be a file, data block, and/or memory contents. The device takes action when the host system data does not match the information in protected storage, such as to log information about the mismatch and/or provide an indication of validation failure, e.g., via an LED and/or display screen output. Further, the comparison may be part of a boot process validation, and the action may prevent the boot process from continuing, or replace an invalid file. Alternatively, the validation may take place at anytime.

Abstract: Systems, methods, and computer-readable storage media are provided for efficient real-time ink stroke smoothing, trajectory prediction, and GPU-leveraged rendering of ink stroke input. First and second ink points are received and an active Bézier approximation is computed based thereupon. Sequentially later in time that the first and second ink points, a third ink point is received. It is determined whether the third ink point adequately fits the active Bézier approximation. Where it is determined that the third ink point adequately fits, an updated active Bézier approximation is computed that includes the first, second and third ink points. Where it is determined that the third ink point fails to adequately fit, a different new Bézier approximation is computed that includes the third ink point but not the first and second ink points. Leveraging a GPU, a smoothed ink stroke based upon the Bézier approximation(s) is rendered.

Abstract: Systems, methods, and computer-readable storage media are provided for efficient real-time ink stroke smoothing, trajectory prediction, and GPU-leveraged rendering of ink stroke input. First and second ink points are received and an active Bézier approximation is computed based thereupon. Sequentially later in time that the first and second ink points, a third ink point is received. It is determined whether the third ink point adequately fits the active Bézier approximation. Where it is determined that the third ink point adequately fits, an updated active Bézier approximation is computed that includes the first, second and third ink points. Where it is determined that the third ink point fails to adequately fit, a different new Bézier approximation is computed that includes the third ink point but not the first and second ink points. Leveraging a GPU, a smoothed ink stroke based upon the Bézier approximation(s) is rendered.

Abstract: The techniques described herein implement a classification process to evaluate information associated with a tool input (e.g., from an input tool such as a pen or a stylus) and a user touch input (e.g., from a finger or a palm of a hand) to determine whether the user touch input is an intended or an unintended touch input. The information evaluated may be associated with an arrival of the tool input relative to an arrival of the user touch input. The information evaluated may also be associated with a movement of the tool input relative to a movement of the user touch input. In various implementations, the techniques may calculate an evaluation score and compare the evaluation score to a confidence classification threshold. If a confident classification cannot be achieved, the techniques further the classification process as more information associated with the inputs is received.