R. Brunelli, O. Mich, and C. M. Modena, "A survey on the automatic indexing of video data," Journal of Visual Computation and Image Representation, vol. 10, no. 2, pp. 78--112, 1999.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....sequence analysis 1. INTRODUCTION This paper presents a mosaic based motion segmentation method for a layered, MPEG 4 compliant coding of video shots. A video shot is defined as an image sequence captured with a single operation of the camera and presenting a continuous action in time and space [1]. A compact representation of a video shot, useful for video compression [2] coding, editing [3] and indexing [1,4 6] is obtained by computing a mosaic of the background and sequences of the foreground moving objects. This representation achieves high compression rates in the transmission of ....

....compliant coding of video shots. A video shot is defined as an image sequence captured with a single operation of the camera and presenting a continuous action in time and space [1] A compact representation of a video shot, useful for video compression [2] coding, editing [3] and indexing [1,4 6], is obtained by computing a mosaic of the background and sequences of the foreground moving objects. This representation achieves high compression rates in the transmission of the sequence, since all the information about the background (which does not change) is processed and sent only once. ....

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Brunelli R, Mich O, Modena CM. A survey on the automatic indexing of video data. Journal of Visual Communication and Image Representation 1999; 10: 78--112

....a multi resolution structure with captures information from each new frame at its highest resolution level. 1. 2 What can mosaics be used for Video mosaicing has recently attracted a growing interest from the subsea robotics community, but also in the fields of automatic indexing of video data [6] , video coding, video editing, and virtual reality [7] In the subsea domain, mosaics of sidescan sonar images are well known. Their construction is relatively simple thank to strong assumptions on the motion of the sensor. Video mosaics of subsea sequences have several applications in marine ....

R. Brunelli, O. Mich, and C. M. Modena. A survey on the automatic indexing of video data. Journal of Visual Communication and Image Representation, 10:78--112, 1999.

....very competitive as evidenced by our experiments on texture and colour keys. The advantages of the proposed technique are substantial, performing well as a standalone fast indexing key, as part of a composite key to filter unsuitable images or as part of a complete standalone indexing system [12]. 5. FIGURES AND TABLES Table 1. The Classification Ranges and Modifiers Percentage Value Rate Modifier 0 25 10 25 50 1 50 75 1 75 100 10 Table 2. Perceived relevance of first 5 hits Table 3. Indexing operation costs per block ( decoding) Algorithm Rank 1 Rank 2 Rank 3 ....

R. Brunelli, O. Mich, and C M. Modena `A survey on the automatic Indexing of video data' Journal of visual communication and Image Representation, 78-112, 1999.

....Terms Content based image indexing, image retrieval, query by statistical features, image database systems. I. INTRODUCTION n the new era of information technology, traditional databases do not provide a satisfactory environment for variant media types such as audio video and still images [10,11,12]. Instead of small text tags, search engines of This work was suppmted in pan by Yarmouk University, Irbid, Jordan and by the Hijjawi Scientific Foundation, Amman, Jordan. M. A. A1 Jatrah is with the Computer Engineering Department, Yarmouk University, Irbid 21163, Jordan (telephone: 962 2 ....

R. Brunelli, O. Mich, and M. Modena, "A survey on the automatic indexing of video data," J. of Visual Communication and Image Representation, vol. 10, pp. 78- 112 1999,

....segmentation and classification is expected. 1 INTRODUCTION There is a series of meaningful questions that a user could ask in a video programme database search and retheval application scenario. Many of these are covered in reviews presented by Aigrain et al. [1] and more recently Brunelli et al. [2]. Also Wang et al. [11] presents an interesting account on semantic content analysis of video data, focussing mainly on audio based media mode. When analysing video content the aim of almost all multimedia retrieval systems is to reduce the socalled semantic gap, normally known as the lack of ....

R. Brunelli, O. Mich, and C.M. Modena, "A survey on the automatic indexing of video data," Visual Comm. and Image Representation, Vol. 10, pp 78--112, 1999.

....soccer match, their time dependent position, or both. Most solutions to video indexing address the how question with a unimodal approach, using the visual [16, 28, 63, 81, 84, 98, 102] auditory [22, 26, 47, 60, 61, 65, 92] or textual modality [12, 33, 103] Good books [25, 32] and review papers [10, 13] on these techniques have appeared in literature. Instead of using one modality, multimodal video indexing strives to automatically classify (pieces of) a video document based on multimodal analysis. Only recently, approaches using combined multimodal analysis were reported [3, 5, 21, 35, 55, 66, ....

....and visual information to answer the how and what question. We extend this by adding the textual modality, and by relating the which question to multimodal analysis. Moreover, we put forward a unifying and multimodal framework. Our work should therefore be seen as an extension to the work of [10, 13, 90]. Combined they form a complete overview of the field of multimodal video indexing. The multimodal video indexing framework is defined in section 2. We view a single video document from the perspective of its author, and discuss the di#erent modalities and granularities involved in video ....

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R. Brunelli, O. Mich, and C.M. Modena. A survey on the automatic indexing of video data. Journal of Visual Communication and Image Representation, 10(2):78--112, 1999.

....of multimedia analysis, now in its relative embryonic infancy. What might be seen as a progression of the previous image work is today s developments in automatic classification and annotation of multimedia material. Reviews are presented by Aigrain et al. [4] and more recently Brunelli et al. [5]. Also Wang et al. [6] presented an account with an acoustic bias. There are many different aspects and approaches to content based multimedia analysis, the end application being an important determining factor. Motivation for contentbased multimedia analysis arises from applications associated ....

R Brunelli, O. Mich, and C.M. Modena, "A survey on the automatic indexing of video data," Visual Comm. and Image Representation, vol. 10, pp. 78--112, 1999.

....soccer match, their time dependent position, or both. Most solutions to video indexing address the how question with a unimodal approach, using the visual [16, 28, 63, 81, 84, 98, 102] auditory [22, 26, 47, 60, 61, 65, 92] or textual modality [12, 33, 103] Good books [25, 32] and review papers [10, 13] on these techniques have appeared in literature. Instead of using one modality, multimodal video indexing strives to automatically classify (pieces of) a video document based on multimodal analysis. Only recently, approaches using combined multimodal analysis were reported [3, 5, 21, 35, 55, 66, ....

....and visual information to answer the how and what question. We extend this by adding the textual modality, and by relating the which question to multimodal analysis. Moreover, we put forward a unifying and multimodal framework. Our work should therefore be seen as an extension to the work of [10, 13, 90]. Combined they form a complete overview of the eld of multimodal video indexing. The multimodal video indexing framework is de ned in section 2. We view a single video document from the perspective of its author, and discuss the di erent modalities and granularities involved in video indexing. ....

[Article contains additional citation context not shown here]

R. Brunelli, O. Mich, and C.M. Modena. A survey on the automatic indexing of video data. Journal of Visual Communication and Image Representation, 10(2):78-112, 1999. 28

....of multimedia analysis, now in its relative embryonic infancy. What might be seen as a progression of the previous image work is today s developments in automatic classification and annotation of multimedia material. Reviews are presented by Aigrain et al. [4] and more recently Brunelli et al. [5]. Also Wang et al. [6] presented an account with an acoustic bias. There are many different aspects and approaches to contentbased multimedia analysis, the end application being an important determining factor. Motivation for content based multimedia analysis arises from applications associated ....

R Brunelli, O. Mich, and C.M. Modena, "A survey on the automatic indexing of video data," Visual Comm. and Image Representation, vol. 10, pp. 78--112, 1999.

....strong connectivity conditions can be applied for clustering, which has the bene ts of computational simplicity. 4.2. 3 Visual Similarity in Home Video Clusters Content based image analysis has addressed the issue of computing similarity between images videos [24] 30] 36] 9] 39] 44] [5], 49] In our problem, a question is that of the visual structure of home video clusters: how similar (resp. dissimilar) are segments that belong to the same (resp. a di erent) cluster Let s i and s j denote the i th and j th segments in a sequence, and let E be a binary r.v. that indicates ....

R. Brunelli, O. Mich, and C.M. Modena, A Survey on the Automatic Indexing of Video Data, Journal of Visual Communication and Image Representation, Vol. 10, pp. 78-112, 1999.

....an expensive and time consuming task. Therefore, automatic video indexing methods are necessary. Most solutions to video indexing use a unimodal approach, i.e. only the visual, auditory, or textual modality is used. Good review papers on these techniques have appeared in literature, e.g. [7]. Instead of using one modality, multimodal video indexing strives to automatically classify (pieces of) a video document based on multimodal analysis. A review of multimodal video indexing is presented in [46] The authors focus on approaches and algorithms available for processing of auditory ....

....available for processing of auditory and visual information. We extend this by adding the textual modality, and by relating the type of indexes one uses for labelling. Moreover, we put forward a unifying and multimodal framework. Our work should therefore be seen as an extension to the work of [7, 46]. Combined they form a complete overview of the field of multimodal video indexing. The multimodal video indexing framework is defined in section 2. This framework forms the basis for structuring the discussion on video document segmentation in section 3. In section 4 the role of conversion and ....

[Article contains additional citation context not shown here]

R. Brunelli, O. Mich, and C. Modena. A survey on the automatic indexing of video data. Journal of Visual Communication and Image Representation, 10(2):78--112, 1999.

....elds. Reliable and convenient access to visual information is then of major interest for an eOEcient use of these databases. This implies indexing and retrieval of visual documents by their content. A great deal of research amount is currently devoted to image and video database management, [AZP96,BMM99]. Nevertheless, it remains hard to easily identify relevant information with regards to a given query, due to the complexity of dynamic scene analysis. Another important aspect of video database management lies in the denition of appropriate similarity measures associated to the description of ....

Brunelli (R.), Mich (O.) et Modena (C.M.). A survey on the automatic indexing of video data. Jal of Visual Communication and Image Representation, vol. 10, 1999, pp. 78112.

....approach currently appears more suited to deal with the variety of dynamic contents involved in non dedicated video bases. In addition, it can benefit from the great deal of research devoted to the definition of tools for content based video indexing based on the extraction of numerical features [1, 3, 5 7]. As far as retrieval with query by example is concerned, the proposed approaches mainly consider global queries [5 7, 16] They exploit a global characterization of video content, considering static (color, texture) or dynamic content (motion) However, from user point of view partial query ....

R. Brunelli, O. Mich, and C.M. Modena. A survey on the automatic indexing of video data. Jal of Vis. Comm. and Im. Repr., 10(2):78--112, 1999.

.... main tasks for automatic indexing of video data, such as shot or high level segmentation, gradual # e ects detection, or key frames extraction, use more or less explicitly the concept of similarity between frames, and are implemented through features extraction and similarity measures computation [7,8].The features extracted to represent an image or a sequence of images through a signature are usually color [9] texture [10] shape [11] or edge descriptors [12] and speci c motion descriptors [13]formoving images. 1.2. What is an image made of When considering an image (or a sequence of ....

....we just implement standard dissimilarity measures, normalized when possible. The implemented options are presented in table 1. For color histograms, wehave selected the four following dissimilarity measures: L # norm [9] which is equivalent to histogram intersection, L # norm [9] # test [8],and LA based on a quadratic form [23] and a similarity matrix between quantized colors. Dissimilarity measures selected for region histograms are L # norm, and Earth Mover s distance which is described in details in [24] For cumulative histograms, we considered, according to [8] L1 norm, ....

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R. Brunelli, O. Mich, and C.M. Modena, \A survey on the automatic indexing of video data," ####### ## ###### ############# ### ##### ############## #######,vol. 10, pp. 78-112, 1999.

....are compared with the current literature and illustrated with real sequences experiments. An example of content based manipulation is also shown. Introduction This paper presents a mosaic based motion segmentation method for content based, MPEG 4 compliant video coding, useful for indexing (Brunelli et al. 1999, Chang et al. 1997) and editing (Giaccone Jones, 1998) The compact representation of a video shot we addopt is composed by a mosaic of the background and sequences of the foreground moving objects. This achieves high compression rates, since all the information about the background (which ....

Brunelli, R.; Mich O. ; & Modena C. M. (1999). A survey on the automatic indexing of video data. Journal of Visual Communication and Image Representation, 10:78--112.

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R. Brunelli, O. Mich, and C. M. Modena, "A survey on the automatic indexing of video data," Journal of Visual Computation and Image Representation, vol. 10, no. 2, pp. 78--112, 1999.

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R. Brunelli, O. Mich, and C.M. Modena, "A survey on the automatic indexing of video data," Journal of Visual Computation and Image Representation, vol.10, no.2, pp.78--112, 1999.

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R. Brunelli, O. Mich, and C. M. Modena. A survey on the automatic indexing of video data. Journal of Visual Communication and Image Representation, 10(2):78--112, June 1999.

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Brunelli, R., Mich, O. & Modena, C. M. (1999), `A survey of the automatic indexing of video data', Journal of Visual Communication and Image Representation 10(2), 78--112.

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R. Brunelli, O. Mich, and C.M. Modena, "A survey on the automatic indexing of video data," Journal of Visual Communication and Image Representation, Vol. 10, No. 2, pp. 78--112, 1999.

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R. Brunelli, O. Mich, and C. M. Modena. A Survey on the Automatic Indexing of Video Data. Journal of Visual Communication and Image Representation, 10:78--112, 1999.

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R. Brunelli, O. Mich, and C. Modena. A survey on the automatic indexing of video data. Journal of Visual Communication and Image Representation, 10(2):78--112, 1999.

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Brunelli R, Mich O, Modena CM (1999) A survey on the automatic indexing of video data. J Vis Commun Image Represent 10(2):78--112

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R. Brunelli, O. Mich, and C. M. Modena, "A survey on the automatic indexing of video data," J. Vis. Commun. Image Represent., vol. 10, no. 2, pp. 78--112, 1999.

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R. Brunelli, et al., "A survey on the automatic indexing of video data," Journal Visual Communication Image Representation, vol. 10, no. 2, pp. 78--112, 1999.

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