Abstract: A method for calculating an estimated hand motion vector of a plurality of images includes selecting a current video frame and a previous video frame from a video stream, dividing the current video frame into a plurality of macroblocks, selecting a subset of macroblocks from the current video frame, comparing the subset of macroblocks to the previous video frame within a two dimensional comparison range to generate a set of motion vectors, calculating a frame motion vector for the current video frame, estimating a steady motion vector for the current video frame by a first-order autoregression, and calculating a hand motion vector for the current video frame by taking a difference between the steady motion vector and the frame motion vector of the current video frame.

Abstract: A digital video image stabilization method features scene change detection, adaptive stabilization in two dimensions, prevention of accumulated-compensation saturation, multi-resolution motion estimation, and compatibility with MPEG video encoding standards. The method uses block-based motion estimation on a selected set of macroblocks, which generates and validates a set of motion vectors, to determine how a digital camcorder or other video recording device is moving; accumulates motion data to estimate and preserve overall motion due to panning while eliminating small variations due to shaking; and resets its accumulated motion data when it detects a scene change. The method uses this information to select a sub-image from a larger image for the selected video frame. When one or more edges of the sub-image approach the edges of the larger image, the method reduces its correction factor to transition smoothly to a faster pan and prevent saturation.

Abstract: A method for calculating an estimated hand motion vector of a plurality of images includes selecting a current video frame and a previous video frame from a video stream, dividing the current video frame into a plurality of macroblocks, selecting a subset of macroblocks from the current video frame, comparing the subset of macroblocks to the previous video frame within a two dimensional comparison range to generate a set of motion vectors, calculating a frame motion vector for the current video frame, estimating a steady motion vector for the current video frame by a first-order autoregression, and calculating a hand motion vector for the current video frame by taking a difference between the steady motion vector and the frame motion vector of the current video frame.

Abstract: A digital video image stabilization method features scene change detection, adaptive stabilization in two dimensions, prevention of accumulated-compensation saturation, multi-resolution motion estimation, and compatibility with MPEG video encoding standards. The method uses block-based motion estimation on a selected set of macroblocks, which generates and validates a set of motion vectors, to determine how a digital camcorder or other video recording device is moving; accumulates motion data to estimate and preserve overall motion due to panning while eliminating small variations due to shaking; and resets its accumulated motion data when it detects a scene change. The method uses this information to select a sub-image from a larger image for the selected video frame. When one or more edges of the sub-image approach the edges of the larger image, the method reduces its correction factor to transition smoothly to a faster pan and prevent saturation.