Abstract: A method to improve the efficiency of the detection and tracking of machine-readable objects is disclosed. The properties of image frames may be pre-evaluated to determine whether a machine-readable object, even if present in the image frames, would be likely to be detected. After it is determined that one or more image frames have properties that may enable the detection of a machine-readable object, image data may be evaluated to detect the machine-readable object. When a machine-readable object is detected, the location of the machine-readable object in a subsequent frame may be determined based on a translation metric between the image frame in which the object was identified and the subsequent frame rather than a detection of the object in the subsequent frame. The translation metric may be identified based on an evaluation of image data and/or motion sensor data associated with the image frames.

Abstract: A barcode decoding system and method are disclosed that use a data-driven classifier for transforming a potentially degraded barcode signal into a digit sequence. The disclosed implementations are robust to signal degradation through incorporation of a noise model into the classifier construction phase. The run-time computational cost is low, allowing for efficient implementations on portable devices. Implementations are disclosed for intelligent preview scaling, barcode-aware autofocus augmentation and multi-scale signal feature extraction.

Abstract: Psychovisual image compression techniques are disclosed that compress pixel data by a fixed compression ratio with little or no perceptual loss of detail. In some implementations, a psychovisual compression process is selected among several psychovisual compression processes based on characteristics of the pixel data. Compression is achieved during encoding by discarding psychovisually unnecessary bits from the pixel data. The psychovisual compression processes can be implemented in hardware and operate on scan lines of pixels captured by the image sensor. The psychovisual compression techniques can be used with image compression techniques to compress further the pixel data.

Abstract: A user interface enables a user to calibrate the position of a three dimensional model with a real-world environment represented by that model. Using a device's sensor, the device's location and orientation is determined. A video image of the device's environment is displayed on the device's display. The device overlays a representation of an object from a virtual reality model on the video image. The position of the overlaid representation is determined based on the device's location and orientation. In response to user input, the device adjusts a position of the overlaid representation relative to the video image.

Abstract: A user interface enables a user to calibrate the position of a three dimensional model with a real-world environment represented by that model. Using a device's sensor suite, the device's location and orientation is determined. A video image of the device's environment is displayed on the device's display. The device overlays a representation of an object from a virtual reality model on the video image. The position of the overlaid representation is determined based on the device's location and orientation. In response to user input, the device adjusts a position of the overlaid representation relative to the video image.

Abstract: The disclosed implementations provide a system and method of detecting skin tone comprising receiving an image; determining a light intensity of the image; converting a color space of each pixel in the image into a converted value based on the light intensity; and selecting a classifier from a plurality of classifiers based on the light intensity; determining for each converted value, using the selected classifier, a probability that the converted value represents a skin tone; and detecting presence of skin tone in the image based on the determined pixel probabilities.

Abstract: A three-dimensional (“3D”) avatar can be automatically created that resembles the physical appearance of an individual captured in one or more input images or video frames. The avatar can be further customized by the individual in an editing environment and used in various applications, including but not limited to gaming, social networking and video conferencing.

Abstract: Systems, methods and computer program products are disclosed for automatic image sharpening. Automatic image sharpening techniques are disclosed that automatically bring a blurred image into focus. Techniques for reducing edge ringing in sharpened images are also disclosed. According to implementations, a computer-implemented method includes determining a normalized entropy of a first image, calculating a correlation target based on the normalized entropy, automatically determining a blur radius of a de-convolution kernel that causes a cosine of a first radial power spectrum of the kernel and a second radial power spectrum of a reconstruction of the first image to approximate the correlation target and generating a second image based on the blur radius.

Abstract: Methods and apparatus for a roof analysis tool for constructing a parameter set, where the parameter set is derived from mapping data for a map region, and where the parameter set describes the roofs for the buildings within the map region. In some cases, the parameter set includes a list of roof type identification values and the respective buildings in the map region for which a given roof type identification value corresponds. The roof analysis tool may operate on a server and work in conjunction with a mobile device, where the mobile device may display map views of a map region such that the map view is based on a three-dimensional model of the map region, and where a portion of the three-dimensional model is based on data generated on the mobile device and a portion of the three-dimensional model is based on data generated on the server.

Abstract: The disclosed implementations provide a system and method of detecting skin tone comprising receiving an image; determining a light intensity of the image; converting a color space of each pixel in the image into a converted value based on the light intensity; and selecting a classifier from a plurality of classifiers based on the light intensity; determining for each converted value, using the selected classifier, a probability that the converted value represents a skin tone; and detecting presence of skin tone in the image based on the determined pixel probabilities.

Abstract: A barcode decoding system and method are disclosed that use a data-driven classifier for transforming a potentially degraded barcode signal into a digit sequence. The disclosed implementations are robust to signal degradation through incorporation of a noise model into the classifier construction phase. The run-time computational cost is low, allowing for efficient implementations on portable devices. Implementations are disclosed for intelligent preview scaling, barcode-aware autofocus augmentation and multi-scale signal feature extraction.

Abstract: A barcode decoding system and method are disclosed that use a data-driven classifier for transforming a potentially degraded barcode signal into a digit sequence. The disclosed implementations are robust to signal degradation through incorporation of a noise model into the classifier construction phase. The run-time computational cost is low, allowing for efficient implementations on portable devices.

Abstract: Systems, methods and computer program products are disclosed for resampling a digital image. According to an implementation, a source image can be presharpened and upsampled to a first upsampled image having a specified image size and a first level of presharpening. The source image is also presharpened and upsampled to a second upsampled image having the specified image size and second level of presharpening that is less than the first level of presharpening. The first and second upsampled images are deblurred. A binary edge mask image is generated from the deblurred, upsampled images. The binary edge mask image is dilated and blurred to generate a deep mask image. The first and second, deblurred upsampled images are blended together using the deep mask image.

Abstract: Among other disclosed subject matter, a method includes obtaining, in a mobile device, power information indicating a detected power of respective signals received from multiple transmitters. The method includes determining a location of the mobile device using a formula that uses: locations of the multiple transmitters, a first function of the power information and a second function of respective locations of the multiple transmitters. The method can include recording the determined location.

Abstract: Customers can use their own mobile devices to pay for products in a “self-service” transaction, without the assistance of a store employee and without the need for the store to provide a self-service checkout kiosk. The customer's device communicates with a server maintained by the store to identify the product(s) being purchased and to provide a digital credential that the server can use to look up financial account information for the customer. The server can process a payment transaction to the financial account and notify the customer's device of the result. In some cases, an employee device can provide product identification for a purchase to the server and associate the customer device with the purchase, allowing the customer to complete the transaction directly with the store server.

Abstract: Psychovisual image compression techniques are disclosed that compress pixel data by a fixed compression ratio with little or no perceptual loss of detail. In some implementations, a psychovisual compression process is selected among several psychovisual compression processes based on characteristics of the pixel data. Compression is achieved during encoding by discarding psychovisually unnecessary bits from the pixel data. The psychovisual compression processes can be implemented in hardware and operate on scan lines of pixels captured by the image sensor. The psychovisual compression techniques can be used with image compression techniques to compress further the pixel data.

Abstract: Systems, methods and computer program products are disclosed for automatic image sharpening. Automatic image sharpening techniques are disclosed that automatically bring a blurred image into focus. Techniques for reducing edge ringing in sharpened images are also disclosed. According to implementations, a computer-implemented method includes determining a normalized entropy of a first image, calculating a correlation target based on the normalized entropy, automatically determining a blur radius of a de-convolution kernel that causes a cosine of a first radial power spectrum of the kernel and a second radial power spectrum of a reconstruction of the first image to approximate the correlation target and generating a second image based on the blur radius.

Abstract: An activity state (e.g., stationary or moving) of an intermittently moving mobile device is classified using sensor measurements provided by one or more on-board sensors. The activity state can be determined by a classifier that exploits the separable log-normal distributions of the short-time variance of sensor measurements. The activity state can provide an external non-correlated indication of movement or stationarity to an on-board navigation engine. The on-board navigation engine can use the activity state to improve tracking performance.

Abstract: One embodiment may take the form of a method of operating a computing device to provide presence based functionality. The method may include operating the computing device in a reduced power state and collecting a first set of data from a first sensor. Based on the first set of data, the computing device determines if an object is within a threshold distance of the computing device and, if the object is within the threshold distance, the device activates a secondary sensor to collect a second set of data. Based on the second set of data, the device determines if the object is a person. If the object is a person, the device determines a position of the person relative to the computing device and executes a change of state in the computing device based on the position of the person relative to the computing device. If the object is not a person, the computing device remains in a reduced power state.

Abstract: One embodiment may take the form of a method of operating a computing device in a reduced power state and collecting a first set of data from at least one sensor. Based on the first set of data, the computing device determines a probability that an object is within a threshold distance of the computing device and, if so, the device activates at least one secondary sensor to collect a second set of data. Based on the second set of data, the device determines if the object is a person. If it is a person, a position of the person relative to the computing device is determined and the computing device changes its state based on the position of the person. If the object is not a person, the computing device remains in a reduced power state.