Abstract: A method for obtaining structural information from a digital image by an electronic device is described. The method includes obtaining a digital image. The method also includes determining a gradient vector for each pixel in a region of interest of the digital image. The method further includes transforming each pixel in the region of interest in accordance with a transform. Transforming each pixel includes determining, for each pixel, a first set of pixels. The first set of pixels includes any pixel along a line that is collinear with or perpendicular to the gradient vector and passes through a pixel location. Transforming each pixel includes incrementing with signed integer values, for each pixel, a first set of values in a transform space corresponding to any of the first set of pixels that are in a first direction of the line.

Abstract: Aspects of the disclosure are related to a touch controller for use in a device having a processor and a touch sensor panel, the touch controller being coupled to the processor and the touch sensor panel, and further comprising: an analog front-end (AFE), wherein the AFE is configured to generate raw touch image data based on electrical signals generated by the touch sensor panel in response to one or more detected touches thereto; a coarse processing element configured to, in response to the processor being set to a sleep mode, coarsely process the raw touch image data to generate sparse data; and an embedded memory configured to store at least the sparse data, wherein the touch controller is configured to transmit a signal to the processor to wake the processor up and transmit the stored sparse data and new touch image data to the processor, wherein the processor performs gesture recognition based on the sparse data and the new touch image data.

Abstract: Aspects of the disclosure are related to a touch controller for use in a device having a processor and a touch sensor panel, the touch controller being coupled to the processor and the touch sensor panel, and further comprising: an analog front-end (AFE), wherein the AFE is configured to generate raw touch image data based on electrical signals generated by the touch sensor panel in response to one or more detected touches thereto; a coarse processing element configured to, in response to the processor being set to a sleep mode, coarsely process the raw touch image data to generate sparse data; and an embedded memory configured to store at least the sparse data, wherein the touch controller is configured to transmit a signal to the processor to wake the processor up and transmit the stored sparse data and new touch image data to the processor, wherein the processor performs gesture recognition based on the sparse data and the new touch image data.

Abstract: A method for tracking an object by an electronic device is described. The method includes detecting an object position in an initial frame to produce a detected object position. The method also includes measuring one or more landmark positions based on the detected object position or a predicted object position. The method further includes predicting the object position in a subsequent frame based on the one or more landmark positions. The method additionally includes determining whether object tracking is lost. The method also includes avoiding performing object detection for the subsequent frame in a case that object tracking is maintained.

Abstract: A method for tracking an object by an electronic device is described. The method includes detecting an object position in an initial frame to produce a detected object position. The method also includes measuring one or more landmark positions based on the detected object position or a predicted object position. The method further includes predicting the object position in a subsequent frame based on the one or more landmark positions. The method additionally includes determining whether object tracking is lost. The method also includes avoiding performing object detection for the subsequent frame in a case that object tracking is maintained.

Abstract: A method for obtaining structural information from a digital image by an electronic device is described. The method includes determining an iris position in a region of interest based on a gradient direction transform. Determining the iris position may include determining a first dimension position and a second dimension position corresponding to a maximum value in the transform space.

Abstract: A method for obtaining structural information from a digital image by an electronic device is described. The method includes obtaining a digital image. The method also includes determining a gradient vector for each pixel in a region of interest of the digital image. The method further includes transforming each pixel in the region of interest in accordance with a transform. Transforming each pixel includes determining, for each pixel, a first set of pixels. The first set of pixels includes any pixel along a line that is collinear with or perpendicular to the gradient vector and passes through a pixel location. Transforming each pixel includes incrementing with signed integer values, for each pixel, a first set of values in a transform space corresponding to any of the first set of pixels that are in a first direction of the line.

Abstract: A method includes capturing an image of a scene that includes a diagram. The method further includes applying functional block recognition rules to image data of the image to recognize functional blocks of the diagram. The functional blocks include at least a first functional block associated with a first computer operation. The method further includes determining whether the functional blocks comply with functional block syntax rules. A functional graph is computer-generated based on the functional blocks complying with the functional block syntax rules. The functional graph corresponds to the diagram, and the functional graph includes the functional blocks.

Abstract: A method for deformable expression detection is disclosed. For each pixel in a preprocessed image, a sign of a first directional gradient component and a sign of a second directional gradient component are combined to produce a combined sign. Each combined sign is coded into a coded value. An expression in an input image is detected based on the coded values.

Abstract: A method for deformable expression detection is disclosed. For each pixel in a preprocessed image, a sign of a first directional gradient component and a sign of a second directional gradient component are combined to produce a combined sign. Each combined sign is coded into a coded value. An expression in an input image is detected based on the coded values.

Abstract: A method includes capturing an image of a scene that includes a diagram. The method further includes applying functional block recognition rules to image data of the image to recognize functional blocks of the diagram. The functional blocks include at least a first functional block associated with a first computer operation. The method further includes determining whether the functional blocks comply with functional block syntax rules. A functional graph is computer-generated based on the functional blocks complying with the functional block syntax rules. The functional graph corresponds to the diagram, and the functional graph includes the functional blocks.