Residual frame

About: Residual frame is a research topic. Over the lifetime, 4443 publications have been published within this topic receiving 68784 citations.

Apparatus for detecting television image movement

Abstract: In an apparatus for detecting movement of a television image in response to frame difference data corresponding to a difference between present frame data and previous frame data, a video signal is divided into a plurality of segmental areas of each frame, a pixel or picture element is selected to represent each of the segmental areas, frame difference data are produced for each of the segmental areas by calculating differences in the position or coordinates of a pixel represent. ative of a segmental area of a previous frame from the respective picture element of the corresponding segmental area in the in the present frame, and each of the calculated differences smaller than a predetermined magnitude, and which would be characteristic of a stationary background portion of the television image, is omitted from the frame difference data.

Motion vector detecting apparatus for determining interframe, predictive error as a function of interfield predictive errors

Abstract: A motion vector detecting apparatus adapted for detecting motion vectors in motion prediction of an interlaced moving picture comprised of sets of picture blocks consisting of a plurality of pixels. In the case of carrying out five motion predictive error calculations of motion vector from current frame to frame to which reference is made, motion vector from odd field of current frame to odd field of frame to which reference is made, motion vector from odd field of current frame to even field of frame to which reference is made, motion vector from even field of current frame to odd field of frame to which reference is made, and motion vector from even field of current frame to even field of frame to which reference is made, output results of accumulators for carrying out calculation of motion vectors for field are used as they are, thus to carry out calculation of motion vectors for frame at the same time.

A Fast and Robust Key Frame Extraction Method for Video Copyright Protection

Abstract: The paper proposes a key frame extraction method for video copyright protection. The fast and robust method is based on frame difference with low level features, including color feature and structure feature. A two-stage method is used to extract accurate key frames to cover the content for the whole video sequence. Firstly, an alternative sequence is got based on color characteristic difference between adjacent frames from original sequence. Secondly, by analyzing structural characteristic difference between adjacent frames from the alternative sequence, the final key frame sequence is obtained. And then, an optimization step is added based on the number of final key frames in order to ensure the effectiveness of key frame extraction. Compared with the previous methods, the proposed method has advantage in computation complexity and robustness on several video formats, video resolution, and so on.

Region based moving image editing system and method

Abstract: One embodiment uses a computer system to define areas with moving image information of interest in a sequence of digital moving image frames. The sequence of digital moving image frames has at least three frames, a first frame, a second frame and a third frame, in time sequence. A set of points identifies the areas with moving image information of interest on the first frame. In the third frame, the areas with moving image information of interest are identified with the set of points. Each point in the set of points has an explicitly defined location in the first frame and an explicitly defined location in the third frame. The location of each point in the first frame corresponds to the same areas with moving image information of interest as each point's location in the second and third frames. For example if one of the points is located at the tip of a runner's left toe in the first frame, then that point will be located at the tip of the runner's left toe in both the second and third frames. The computer system automatically computes the location of the areas of interest in the second frame.