Macroblock Classification Method for Video Applications Involving Motions
In this paper, a macroblock classification method is proposed for various video processing applications involving motions. Based on the analysis of the Motion Vector field in the compressed video, we propose to classify Macroblocks of each video frame into different classes and use this class information to describe the frame content. We demonstrate that this low-computation-complexity method can efficiently catch the characteristics of the frame. Based on the proposed macroblock classification, we further propose algorithms for different video processing applications, including shot change detection, motion discontinuity detection, and outlier rejection for global motion estimation. Experimental results demonstrate that the methods based on the proposed approach can work effectively on these applications.
Code (0)
등록된 구현이 없습니다.
Tasks
Change DetectionClassificationGeneral ClassificationMotion EstimationSimilar Papers 제목 키워드 기반
Spatio-temporal prediction in video coding by spatially refined motion compensation
The purpose of this contribution is to introduce a new method of signal prediction in video coding. Unlike most existent prediction methods that either use temporal or use spatial correlations to generate the prediction …
DecoderMotion CompensationPredictionDigital Video Manipulation Detection Technique Based on Compression Algorithms
Digital images and videos play a very important role in everyday life. Nowadays, people have access the affordable mobile devices equipped with advanced integrated cameras and powerful image processing applications. Tech…
Loss Switching Fusion with Similarity Search for Video Classification
From video streaming to security and surveillance applications, video data play an important role in our daily living today. However, managing a large amount of video data and retrieving the most useful information for t…
ClassificationClusteringGeneral ClassificationScene Understanding+1Video Classification With CNNs: Using The Codec As A Spatio-Temporal Activity Sensor
We investigate video classification via a two-stream convolutional neural network (CNN) design that directly ingests information extracted from compressed video bitstreams. Our approach begins with the observation that a…
ClassificationCloud ComputingCPUGeneral Classification+3AccMPEG: Optimizing Video Encoding for Video Analytics
With more videos being recorded by edge sensors (cameras) and analyzed by computer-vision deep neural nets (DNNs), a new breed of video streaming systems has emerged, with the goal to compress and stream videos to remote…
CPUobject-detectionObject DetectionSemantic Segmentation