Abstract: An electronic device and associated method place a sticker near a facial region in a digital image. The method detects 2D positions of facial features from a 2D digital image, and calculates a projection matrix from a predetermined 3D reference model having predefined facial feature points that correspond to the 2D detected facial features. The method then selects a digital sticker, and for each corner of the selected digital sticker, uses the projection matrix to transform 3D positions of the corner to corresponding positions on the 2D digital image. The method calculates a refinement matrix defining a correlation of each corner of the selected digital sticker to anchor points in the 2D digital image. Using the refinement matrix, the method calculates updated projected 2D positions and displays the selected sticker on the 2D digital image based on the updated projected 2D positions for each corner point.

Abstract: An electronic device and associated method place a sticker near a facial region in a digital image. The method detects 2D positions of facial features from a 2D digital image, and calculates a projection matrix from a predetermined 3D reference model having predefined facial feature points that correspond to the 2D detected facial features. The method then selects a digital sticker, and for each corner of the selected digital sticker, uses the projection matrix to transform 3D positions of the corner to corresponding positions on the 2D digital image. The method calculates a refinement matrix defining a correlation of each corner of the selected digital sticker to anchor points in the 2D digital image. Using the refinement matrix, the method calculates updated projected 2D positions and displays the selected sticker on the 2D digital image based on the updated projected 2D positions for each corner point.

Abstract: A method for tracking an object in a plurality of frames includes obtaining a contour of an object in a frame. For each remaining frame among the plurality of frames, the following steps are performed. A probability map generator generates a plurality of probability maps containing probability values for one or more pixels for a current frame. A contour is estimated for the current frame based on the plurality of probability maps. User input is obtained for refining the estimated contour. Based on the user input, one or more local regions to be added and/or removed are identified and recorded in a local region list. The local region list is maintained and updated during the tracking process and is used together with the probability map generator.

Abstract: Various embodiments are disclosed for performing object tracking. One embodiment is a method for tracking an object in a plurality of frames, comprising obtaining a reference contour of an object in a reference frame and estimating, for a current frame after the reference frame, a contour of the object. The method further comprises comparing the reference contour with the estimated contour and determining at least one local region of the reference contour in the reference frame based on a difference between the reference contour and the estimated contour. Based on the difference, at least one corresponding region of the current frame is determined.

Abstract: Various embodiments are disclosed for selecting a region of interest within an object. One embodiment is a method for editing a digital image in an image editing device. The method comprises obtaining a first position within a digital image, the first position being specified by a pointer. The method further comprises defining a first selection region based on the first position and obtaining a second position within the digital image, the second position being specified by the pointer. The method further comprises determining movement of the pointer between the first position and the second position and predicting future movement by the pointer based on the determined movement. Based on the determined movement and the predicted future movement, the first selection region is expanded to define a second selection region.

Abstract: A liveness detection method comprising: receiving plural pictures of a video stream comprising a face and an adjacent background; determining motion of the face and the background, the motion determined over the plural pictures; comparing the motion between the face and the background; and determining whether the face corresponds to an actual, live user or an image of the user based on the comparison, the determinations performed by a processor.

Abstract: A method for tracking an object in a plurality of frames includes obtaining a contour of an object in a frame. For each remaining frame among the plurality of frames, the following steps are performed. A probability map generator generates a plurality of probability maps containing probability values for one or more pixels for a current frame. A contour is estimated for the current frame based on the plurality of probability maps. User input is obtained for refining the estimated contour. Based on the user input, one or more local regions to be added and/or removed are identified and recorded in a local region list. The local region list is maintained and updated during the tracking process and is used together with the probability map generator.

Abstract: Various embodiments are disclosed for performing object tracking. One embodiment is a system for tracking an object in a plurality of frames, comprising a probability map generator configured to generate a probability map by estimating probability values of pixels in the frame, wherein the probability of each pixel corresponds to a likelihood of the pixel being located within the object. The system further comprises a contour model generator configured to identify a contour model of the object based on a temporal prediction method, a contour weighting map generator configured to derive a contour weighting map based on thickness characteristics of the contour model, a tracking refinement module configured to refine the probability map according to weight values specified in the contour weighting map, and an object tracker configured to track a location of the object within the plurality of frames based on the refined probability map.

Abstract: A liveness detection method comprising: receiving plural pictures of a video stream comprising a face and an adjacent background; determining motion of the face and the background, the motion determined over the plural pictures; comparing the motion between the face and the background; and determining whether the face corresponds to an actual, live user or an image of the user based on the comparison, the determinations performed by a processor.

Abstract: Various embodiments are disclosed for selecting a region of interest within an object. One embodiment is a method for editing a digital image in an image editing device. The method comprises obtaining a first position within a digital image, the first position being specified by a pointer. The method further comprises defining a first selection region based on the first position and obtaining a second position within the digital image, the second position being specified by the pointer. The method further comprises determining movement of the pointer between the first position and the second position and predicting future movement by the pointer based on the determined movement. Based on the determined movement and the predicted future movement, the first selection region is expanded to define a second selection region.

Abstract: Various embodiments are disclosed for performing object tracking. One embodiment is a system for tracking an object in a plurality of frames, comprising a probability map generator configured to generate a probability map by estimating probability values of pixels in the frame, wherein the probability of each pixel corresponds to a likelihood of the pixel being located within the object. The system further comprises a contour model generator configured to identify a contour model of the object based on a temporal prediction method, a contour weighting map generator configured to derive a contour weighting map based on thickness characteristics of the contour model, a tracking refinement module configured to refine the probability map according to weight values specified in the contour weighting map, and an object tracker configured to track a location of the object within the plurality of frames based on the refined probability map.

Abstract: Various embodiments are disclosed for performing object tracking. One embodiment is a method for tracking an object in a plurality of frames, comprising obtaining a reference contour of an object in a reference frame and estimating, for a current frame after the reference frame, a contour of the object. The method further comprises comparing the reference contour with the estimated contour and determining at least one local region of the reference contour in the reference frame based on a difference between the reference contour and the estimated contour. Based on the difference, at least one corresponding region of the current frame is determined.

Abstract: A liveness detection method comprising: receiving plural pictures of a video stream comprising a face and an adjacent background; determining motion of the face and the background, the motion determined over the plural pictures; comparing the motion between the face and the background; and determining whether the face corresponds to an actual, live user or an image of the user based on the comparison, the determinations performed by a processor.

Abstract: Systems and methods for generating a summary of photos from a plurality of received photos are described. The received photos are classified according to predefined attributes. Two or more of the categories are selected, and a ratio value is received from a user relating to the two or more of the categories. Photos are selected from among the photos in the two or more categories based on the specified ratio and based on sorting the received photos according to time information. The selected photos comprising the summary of photos are displayed.

Abstract: Systems and methods for generating a summary of photos from a plurality of received photos are described. The received photos are classified according to predefined attributes. Two or more of the categories are selected, and a ratio value is received from a user relating to the two or more of the categories. Photos are selected from among the photos in the two or more categories based on the specified ratio and based on sorting the received photos according to time information. The selected photos comprising the summary of photos are displayed.