Motion Detection in Compressed Video Using Macroblock Classification
نویسنده
چکیده
In this paper, to detect the moving objects between frames in compressed video and to obtain the best compression video and the noiseless video. We describe a video in which frames by classifying macroblocks (MB), and describe motion estimation (ME), motion vector field (MV) and motion compensation (MC). we propose to classify Macroblocks of each video frame into different classes and use this class information to describe the frame content based on the motion vector. MB class information video applications such as shot change detection, motion discontinuity detection, Outlier rejection for global motion estimation. To reduce the noise and to improve the clarity of the compressed video by using contrast limited adaptive histogram equalization (CLAHE) Algorithm.
منابع مشابه
MPEG-2 Compressed-Domain Algorithms for Video Analysis
This paper presents new algorithms for extracting metadata from video sequences in the MPEG-2 compressed domain. Three algorithms for efficient low-level metadata extraction in preprocessing stages are described. The first algorithm detects camera motion using the motion vector field of an MPEG-2 video. The second method extends the idea of motion detection to a limited region of interest, yiel...
متن کاملSPIE Conference on Multimedia Storage and Archiving Systems
Fast and eecient storage, indexing, browsing, and retrieval of video is a necessity for the development of various multimedia database applications. This can be achieved by analyzing the video directly in the compressed domain, thereby avoiding the overhead of decompressing video into individual frames in the pixel domain. Our compressed domain parsing of video performs shot change detection an...
متن کاملShot Boundary Detection Using Macroblock Prediction Type Information
The increasing availability and use of digital video has led to a high demand for efficient video analysis techniques. The starting point in video browsing and retrieval systems is the low-level analysis of video content, especially the segmentation of video content into shots. In this paper, we propose a method for automatic video indexing based on the macroblock prediction type information of...
متن کاملCompressed-domain video classification with deep neural networks: "There's way too much information to decode the matrix"
We investigate video classification via a 3D deep convolutional neural network (CNN) that directly ingests compressed bitstream information. This idea is based on the observation that video macroblock (MB) motion vectors (that are very compact and directly available from the compressed bitstream) are inherently capturing local spatio-temporal changes in each video scene. Our results on two stan...
متن کاملEfficient MPEG Compressed Video Analysis Using Macroblock Type Information
Efficient indexing methods are required to handle the rapidly increasing amount of visual information within video databases. Video analysis that partitions the video into clips or extracts interesting frames is an important preprocessing step for video indexing. In this paper, we develop a novel method for video analysis using the macroblock (MB) type information of MPEG compressed video bitst...
متن کامل