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Inter frame

About: Inter frame is a research topic. Over the lifetime, 4154 publications have been published within this topic receiving 63549 citations.


Papers
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Patent
30 Jun 1998
TL;DR: In this paper, a method and apparatus for encoding a video sequence of frames is described, where each frame in the video sequence is organized in blocks of pixels and a scene change is detected when a current frame is substantially different from a previous frame.
Abstract: A method and apparatus is described for encoding a video sequence of frames. Each frame in the video sequence is organized in blocks of pixels. A scene change is detected when a current frame in the video sequence is substantially different from a previous frame. When it is determined that the current frame is the change in scene, the current frame is coded to be an intra frame with each block of pixels of the intra frame is being an intra-coded block. Coding the sequence of frames produces a compressed bit stream having a coded intra frame at each scene change. Each coded intra frame provides an access point in the bit stream from which a storyboard of the scenes in the video sequence can be generated.

25 citations

Patent
29 Jun 2001
TL;DR: In this article, a Markov model of packet transmission losses is used to determine a tradeoff of the intra-coded frame rate with a repeated predictively coded frame rate to maximize the probability of correct frame reconstruction.
Abstract: Motion compensation of real-time video for transmission over a packetized network is controlled by maximization of the probability of correct frame reconstruction according to a Markov model of packet transmission losses. The control determines a tradeoff of the intra-coded frame rate with a repeated predictively-coded frame rate.

25 citations

Journal ArticleDOI
TL;DR: This paper proposes a novel Wyner-Ziv successive refinement approach to improve the motion compensation accuracy and the overall compression efficiency of Wyner -Ziv video coding.
Abstract: Wyner-Ziv coding enables low complexity video encoding with the motion estimation procedure shifted to the decoder. However, the accuracy of decoder motion estimation is often low, due to the absence of the input source frame (at the decoder). In this paper, we propose a novel Wyner-Ziv successive refinement approach to improve the motion compensation accuracy and the overall compression efficiency of Wyner-Ziv video coding. Our approach encodes each frame by multiple Wyner-Ziv coding layers and uses the progressively refined reconstruction frame to guide the motion estimation for progressively improved accuracy. The proposed approach yields competitive results against state-of-the-art low complexity Wyner-Ziv video coding approaches, and can gain up to 3.8dB over the conventional Wyner-Ziv video coding approach and up to 1.5dB over the previous bitplane-based refinement approach. Furthermore, this paper also presents the rate distortion analysis and the performance comparison of the proposed approach and conventional approaches. The rate distortion performance loss (due to performing decoder motion estimation) is at most 2.17dB (or equivalently 14nats/pixel) in our scheme according to our analysis, but can be more than 6dB in the conventional approach according to previous research. For the simplified two-layers case of our approach, we derive the optimal subsampling ratio in the sense of rate distortion performance. We also extend our analysis and conclusions from P frame to B frame. Finally, we verify our analysis by experimental results.

25 citations

Journal ArticleDOI
TL;DR: This study proposes the use of graph matching (GM) to enable 3D motion capture for Indian sign language recognition and demonstrates that the approach increases the accuracy of recognizing signs in continuous sentences.
Abstract: A machine cannot easily understand and interpret three-dimensional (3D) data. In this study, we propose the use of graph matching (GM) to enable 3D motion capture for Indian sign language recognition. The sign classification and recognition problem for interpreting 3D motion signs is considered an adaptive GM (AGM) problem. However, the current models for solving an AGM problem have two major drawbacks. First, spatial matching can be performed on a fixed set of frames with a fixed number of nodes. Second, temporal matching divides the entire 3D dataset into a fixed number of pyramids. The proposed approach solves these problems by employing interframe GM for performing spatial matching and employing multiple intraframe GM for performing temporal matching. To test the proposed model, a 3D sign language dataset is created that involves 200 continuous sentences in the sign language through a motion capture setup with eight cameras.The method is also validated on 3D motion capture benchmark action dataset HDM05 and CMU. We demonstrated that our approach increases the accuracy of recognizing signs in continuous sentences.

25 citations

Patent
09 May 2005
TL;DR: Temporal classified filtering as discussed by the authors encodes image data by applying filters assigned to classes of pixels in a target frame to predict values for the pixels, which are classified based on their associated motion vectors and position the filters on the reference frame.
Abstract: Temporal classified filtering encodes image data by applying filters assigned to classes of pixels in a target frame to predict values for the pixels. The pixels are classified based on their associated motion vectors and the motion vectors are used to position the filters on the reference frame. Prediction error values are also calculated. The filters, motion vectors, and prediction errors represent the pixels in the encoded image data. The reference frame may be a past or future frame of the image data, and multiple reference frames of various combinations of past and future frames may be used. The filters for multiple reference frames are three-dimensional comprising a two-dimensional filter for each reference frame. The filters ma be pre-determined or generated as the frames are encoded. The image data is recreated by applying the filters to the reference frames and correcting the resulting predictions with the prediction error values.

25 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202324
202272
202162
202084
2019110
201897