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Journal ArticleDOI

A fuzzy theoretic approach for video segmentation using syntactic features

01 Nov 2001-Pattern Recognition Letters (Elsevier Science Inc.)-Vol. 22, Iss: 13, pp 1359-1369
TL;DR: Experimental results have shown that the proposed scheme for fuzzification of the frame-to-frame property difference values using the Rayleigh distribution can detect changes reliably.
Abstract: This paper is concerned with the development of a fuzzy-logic-based framework for segmentation of video sequences. We have proposed a scheme for fuzzification of the frame-to-frame property difference values using the Rayleigh distribution. The difference values have been characterized by fuzzy terms like small, significant, large, etc. These terms have been used to design fuzzy rules for detecting abrupt changes and gradual changes. Fuzzy rules have provided a mechanism for integrating evidences based on different properties. The decompositional inference strategy has been used for fuzzy reasoning over the set of fuzzy rules. Gradual changes have been further classified as fade-in, fade-out and others (including dissolves, wipes, etc). Experimental results have shown that the proposed scheme can detect changes reliably.
Citations
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Journal ArticleDOI
01 May 2008
TL;DR: This paper surveys the video classification literature and finds that features are drawn from three modalities - text, audio, and visual - and that a large variety of combinations of features and classification have been explored.
Abstract: There is much video available today. To help viewers find video of interest, work has begun on methods of automatic video classification. In this paper, we survey the video classification literature. We find that features are drawn from three modalities - text, audio, and visual - and that a large variety of combinations of features and classification have been explored. We describe the general features chosen and summarize the research in this area. We conclude with ideas for further research.

329 citations


Cites background or methods from "A fuzzy theoretic approach for vide..."

  • ...[63] detect shot changes as well as shot transition types using a fuzzy-logic-based approach [58]....

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  • ...videos, and even within the same video, no particular value may correctly identify all shot changes [58]....

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Journal ArticleDOI
TL;DR: Experimental results show that the proposed fuzzy color histogram-based shot-boundary detection algorithm effectively detects shot boundaries and reduces false alarms as compared to the state-of-the-art shot- boundary detection algorithms.
Abstract: We present a fuzzy color histogram-based shot-boundary detection algorithm specialized for content-based copy detection applications The proposed method aims to detect both cuts and gradual transitions (fade, dissolve) effectively in videos where heavy transformations (such as cam-cording, insertions of patterns, strong re-encoding) occur Along with the color histogram generated with the fuzzy linking method on L*a*b* color space, the system extracts a mask for still regions and the window of picture-in-picture transformation for each detected shot, which will be useful in a content-based copy detection system Experimental results show that our method effectively detects shot boundaries and reduces false alarms as compared to the state-of-the-art shot-boundary detection algorithms

88 citations


Cites methods from "A fuzzy theoretic approach for vide..."

  • ...A scene-break detection approach based on linear prediction model is proposed in [4]....

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Journal ArticleDOI
TL;DR: A fuzzy logic approach to integrate hybrid features for detecting shot boundaries inside general videos by using publicly available test data set from Carleton University and demonstrating that the proposed algorithm outperforms the representative existing algorithms in terms of the precision and recall rates.
Abstract: Video temporal segmentation is normally the first and important step for content-based video applications. Many features including the pixel difference, colour histogram, motion, and edge information etc. have been widely used and reported in the literature to detect shot cuts inside videos. Although existing research on shot cut detection is active and extensive, it still remains a challenge to achieve accurate detection of all types of shot boundaries with one single algorithm. In this paper, we propose a fuzzy logic approach to integrate hybrid features for detecting shot boundaries inside general videos. The fuzzy logic approach contains two processing modes, where one is dedicated to detection of abrupt shot cuts including those short dissolved shots, and the other for detection of gradual shot cuts. These two modes are unified by a mode-selector to decide which mode the scheme should work on in order to achieve the best possible detection performances. By using the publicly available test data set from Carleton University, extensive experiments were carried out and the test results illustrate that the proposed algorithm outperforms the representative existing algorithms in terms of the precision and recall rates.

76 citations


Cites background or methods from "A fuzzy theoretic approach for vide..."

  • ...Previous research [4] reveals that the value of HIi varies within [0, 1], and the closer to 1, the larger the difference between the two adjacent frames....

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  • ...[4], the feature of edge pixel count is proposed for shot cut detection, where Sobel edge detector is used....

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Journal ArticleDOI
TL;DR: This work proposes a new approach to the background subtraction method which operates in the colour space and manages the colour information in the segmentation process to detect and eliminate noise.
Abstract: Variants of the background subtraction method are broadly used for the detection of moving objects in video sequences in different applications. In this work we propose a new approach to the background subtraction method which operates in the colour space and manages the colour information in the segmentation process to detect and eliminate noise. This new method is combined with blob-level knowledge associated with different types of blobs that may appear in the foreground. The idea is to process each pixel differently according to the category to which it belongs: real moving objects, shadows, ghosts, reflections, fluctuation or background noise. Thus, the foreground resulting from processing each image frame is refined selectively, applying at each instant the appropriate operator according to the type of noise blob we wish to eliminate. The approach proposed is adaptive, because it allows both the background model and threshold model to be updated. On the one hand, the results obtained confirm the robustness of the method proposed in a wide range of different sequences and, on the other hand, these results underline the importance of handling three colour components in the segmentation process rather than just the one grey-level component.

67 citations


Cites methods from "A fuzzy theoretic approach for vide..."

  • ...The approach proposed is adaptive, because it allows both the background model and threshold model to be updated....

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  • ...…detecting moving objects based, for example, on statistical methods (Horprasert et al., 1999; Lee, 2005; Stauffer and Grimson, 1999), fuzzy logic (Jadon et al., 2001), the subtraction of consecutive frames (Lipton et al., 1998), optical flow (Wang et al., 2003), genetic algorithms (Kim and Park,…...

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Book ChapterDOI
01 Jan 2015
TL;DR: This paper presents different approaches to shot boundary detection problem, and shows how segmentation plays an important role in digital media processing, pattern recognition, and computer vision.
Abstract: 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.

47 citations

References
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Journal ArticleDOI
TL;DR: The approach proposed here is inspired and influenced by well established video production processes and is used to classify the transition effects used in video and to design automatic edit effect detection algorithms.
Abstract: Effective and efficient tools for segmenting and content-based indexing of digital video are essential to allow easy access to video-based information. Most existing segmentation techniques do not use explicit models of video. The approach proposed here is inspired and influenced by well established video production processes. Computational models of these processes are developed. The video models are used to classify the transition effects used in video and to design automatic edit effect detection algorithms. Video segmentation has been formulated as a production model based classification problem. The video models are also used to define segmentation error measures. Experimental results from applying the proposed technique to commercial cable television programming are presented.

223 citations

Proceedings Article
30 May 1997
TL;DR: This paper presents a method for obtaining automatically a macro-segmentation in sequences based on the application of rules expressing the local (in time) clues which are given by the medium contents to enable identiication of more macroscopical changes.
Abstract: EEcient and reliable methods for the segmentation of the image part of a video into shots have been proposed. In actual motion picture or video documents, there can often be 500 to 1000 shots per hour. Thus, if one wants to enable quick browsing of the video contents, quick positioning in the document for interactive viewing, or if one wants to automatically construct abstracts of the document, it is necessary to nd more macroscopic time objects, for instance larger sequences constituting a narrative unit or sharing the same setting. In this paper, we present a method for obtaining automatically such a macro-segmentation in sequences. This method is based on the application of rules expressing the local (in time) clues which are given by the medium contents to enable identiication of more macroscopical changes. We describe how the results from these rules can be combined to obtain a macro-segmentation, and to extract particularly important representative images. We give arguments for the choice of such a general purpose medium-based approach compared to approaches based on modelling speciic types of contents, and present results from its automatic application to a limited sample of documents. This research was conducted under support from the french Minist ere de la Culture et de la Francophonie.

118 citations

Journal ArticleDOI
TL;DR: A novel method is derived to classify the dominant camera motions in video shots by analyzing the optical flow in a decomposed manner and is efficient and effective because only some mean values and standard deviations are used.
Abstract: With the fast growth of video sources, efficient video classification and management is becoming more and more important. Video partitioning and video feature extraction are two of the key issues in video classification. In this paper, we introduce our innovative approaches to scene change detection and camera motion extraction.The video partitioning process involves the detection of boundaries between uninterrupted segments (video shots) of scenes. Shot boundaries can be classified into two categories, gradual transition and instantaneous change (called a camera break). Detection of a gradual transition is considered to be a difficult problem. Few methods have been reported for gradual transition detection. We discuss an efficient method which is calledStep-variable.In this paper, a novel method is derived to classify the dominant camera motions in video shots. The method is to analyze the optical flow in a decomposed manner. Images are divided into subregions according to our camera model. The projectedxandycomponents of optical flow are analyzed separately in the different subregions of the images. Different camera motions are recognized by comparing the computed result with the prior known patterns. Our method is efficient and effective because only some mean values and standard deviations are used. The analysis and a detailed description of our method are presented in this paper. Experimental results are given to show the effectiveness of the proposed method.

106 citations

Journal ArticleDOI
TL;DR: A system allowing content-based annotation and querying in video databases, which automatically splits a video into a sequence of shots, extracts a few representative frames from each shot and computes r-frame descriptors based on color, texture and motion.
Abstract: The increasing development of advanced multimedia applications requires new technologies for organizing and retrieving by content databases of still digital images or digital video sequences. To this aim image and image sequence contents must be described and adequately coded. In this paper we describe a system allowing content-based annotation and querying in video databases. No user action is required during the database population step. The system automatically splits a video into a sequence of shots, extracts a few representative frames (said r-frames) from each shot and computes r-frame descriptors based on color, texture and motion. Queries based on one or more features are possible. Very interesting results obtained during the severe tests the system was subjected to are reported and discussed.

100 citations

Proceedings Article
01 Oct 1999
TL;DR: A general framework to evaluate and compare several temporal video segmentation algorithms and some solutions to these problems are given in this study and are applied for evaluating different methods developed in various contexts.
Abstract: This paper proposes a general framework to evaluate and compare several temporal video segmentation algorithms. The problems that must be solved to confront different methods summarize as gathering a common content set to test the methods, building a reference segmentation, establishing the rules to match the results with the reference, and providing a quality measure. Some solutions to these problems are given in this study and are applied for evaluating different methods developed in various contexts. The paper concludes by presenting results obtained on practical tests. This study was made by a work group of AIM (Multimedia Indexation Action) Working Group 10 of the ISIS Coordinated Research Program.

46 citations