A Classification Approach to Video Shot Boundary Detection (original) (raw)
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Video data management and information …, 2005
The increasing use of multimedia streams nowadays necessitates the development of efficient and effective methodologies for manipulating databases storing this information. Moreover, in its first stage, content-based access to video data requires parsing of each video stream into its building blocks. The video stream consists of a number of shots, each one a sequence of frames pictured using a single camera. Switching from one camera to another indicates the transition from a shot to the next one. Therefore, the detection of these transitions, known as scene change or shot boundary detection, is the first step in any video-analysis system. A number of proposed techniques for solving the problem of shot boundary detection exist, but the major criticisms to them are their inefficiency and lack of reliability. The reliability of the scene change detection stage is a very significant requirement because it is the first stage in any video retrieval system; thus, its performance has a direct impact on the performance of all other stages. On the other hand, efficiency is also crucial due to the voluminous amounts of information found in video streams. This chapter proposes a new robust and efficient paradigm capable of detecting scene changes on compressed MPEG video data directly. This paradigm constitutes the first part of a Video Contentbased Retrieval (VCR) system that has been designed at Old Dominion University. At first, an abstract representation of the compressed video stream, known as the DC
An integrated method for video shot boundary detection
Proceedings of the IEEE SoutheastCon 2010 (SoutheastCon), 2010
Video shot boundary detection, which segments a video by detecting boundaries between camera shots, is usually the first and important step for content-based video retrieval. This paper investigates methods which are effective in detecting abrupt transitions and gradual transitions, respectively, and proposes an integration scheme to combine their results, aiming to detect both types of transitions.
Video Shot Boundary Detection Algorithm
Lecture Notes in Computer Science, 2006
We present a newly developed algorithm for automatically segmenting videos into basic shot units. A basic shot unit can be understood as an unbroken sequence of frames taken from one camera. At first we calculate the frame difference by using the local histogram comparison, and then we dynamically scale the frame difference by Log-formula to compress and enhance the frame difference. Finally we detect the shot boundaries by the newly proposed shot boundary detection algorithm which it is more robust to camera or object motion, and many flashlight events. The proposed algorithms are tested on the various video types and experimental results show that the proposed algorithm are effective and reliably detects shot boundaries.
Dokuz Eylül University video shot boundary detection at TRECVID 2006
Proceedings of the TREC Video Retrieval …, 2006
In this study we described our participation in the NIST TRECVID 2006 evaluation for Shot Boundary Determination task with 10 submissions. We have used a method based on histogram differences for cut and gradual transition detection. Both the details of our approach used in the SBD task submissions and effects of using different threshold & skip frame intervals on evaluation results are presented.
Evaluating and combining digital video shot boundary detection algorithms
2000
The development of standards for video encoding coupled with the increased power of computing mean that content-based manipulation of digital video information is now feasible. Shots are a basic structural building block of digital video and the boundaries between shots need to be determined automatically to allow for content-based manipulation. A shot can be thought of as continuous images from one camera at a time. In this paper we examine a variety of automatic techniques for shot boundary detection that we have implemented and evaluated on a baseline of 720,000 frames (8 hours) of broadcast television. This extends our previous work on evaluating a single technique based on comparing colour histograms. A description of each of our three methods currently working is given along with how they are evaluated. It is found that although the different methods have about the same order of magnitude in terms of effectiveness, different shot boundaries are detected by the different methods. We then look at combining the three shot boundary detection methods to produce one output result and the benefits in accuracy and performance that this brought to our system. Each of the methods were changed from using a static threshold value for three unconnected methods to one using three dynamic threshold values for one connected method. In a final summing up we look at the future directions for this work.
Video Shot Boundary Detection Techniques
2014
Shot boundary detection (SBD) is the basis of revealing even higher levels of the hierarchical video structure. If we advance further from the scene level, we can try to extract even higher-level semantical information from the video by using the shot boundary information. The next structural level above the shot and scene levels in news are videos, story level which contains stories that are made of several scenes. The story boundaries thus usually overlap with some of the scene boundaries, so gathering information on the shot boundaries and scene boundaries help to solve the problem. This bottom-up approach might help us eventually to narrow the semantic gap a little bit more. Knowing the shot boundaries is also crucial for some lower-level feature extraction methods. For example to figure the system which solve the camera movement based on the video data and differences between consecutive frames. This camera movement detection is naturally sensible only inside shot boundaries si...
Video Shot Boundary Detection: A Review
Advances in Intelligent Systems and Computing, 2015
Video image processing is a technique to handle the video data in an effective and efficient way. It is one of the most popular aspects in the video and image based technologies such as surveillance. Shot change boundary detection is also one of the major research areas in video signal processing. Previous works have developed various algorithms in this domain. In this paper, a brief literature survey is presented that establishes an overview of the works that has been done previously. In this paper we have discussed few algorithms that were proposed previously which also includes histogram based, DCT based and motion vector based algorithms as well as their advantages and their limitations.
Evaluation of automatic shot boundary detection on a large video test suite
1999
The challenge facing the indexing of digital video information in order to support browsing and retrieval by users, is to design systems that can accurately and automatically process large amounts of heterogeneous video. The segmentation of video material into shots and scenes is the basic operation in the analysis of video content. This paper presents a detailed evaluation of a histogram-based shot cut detector based on eight hours of TV broadcast video. Our observations are that the selection of similarity thresholds for determining shot boundaries in such broadcast video is difficult and necessitates the development of systems that employ adaptive thresholding in order to address the huge variation of characteristics prevalent in TV broadcast video.
Efficient Shot Boundary Detection with Multiple Visual Representations
Mobile Information Systems, 2022
Due to the unlimited growth of video-capturing devices and media, searching and finding a particular video in this huge database becomes a laborious as well as expensive task. Information-rich shots are the inevitable factor of the content-based video processing (CBVP) system. Hence, shot boundary detection (SBD) becomes the basic step of all content-based video retrieval processes.)e accuracy of the existing SBD methods highly suffers from false positives and false negatives due to the presence of multiple variants. An efficient SBD method with multiple invariant features is proposed in this paper. A right combination of invariant features such as edge change ratio (ECR), colour layout descriptor (CLD), and scale-invariant feature transform (SIFT) key point descriptors helped to improve the accuracy level of SBD. As the selected features are invariant to most of the variants in video frames, such as illuminance changes, motion, scaling, and rotation, a markable reduction in false detection is possible. Support vector machine (SVM) classifier is used for the classification of frames into transition frames and shot frames.)is proposed method is experimented and analysed with the standard SBD dataset TRECVid 2007 videos.)e experimental results are compared with some state-of-art methods, and our method shows better performance with a 97% of F1 score.
Video Shot Boundary Detection Using Various Techniques
2015
Shot and classification is first and foremost step for further analysis of video content. A Shot is defined as a set of frames from a single camera. Processing of video and image facilitates better understanding of the scene that it describe. It is a fundamental component of a number of technologies like video surveillance, robotics etc .A scene is a collection of one or more shots focusing on one or more object of interest. various shot boundary methods have been developed which can detect cut and gradual shot simultaneously.