Review of Image and Video Indexing Techniques

Idris, Fayez M.; Panchanathan, S.

doi:10.1006/jvci.1997.0355

Cited by 216 publications

(84 citation statements)

References 88 publications

(51 reference statements)

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“…Some video segmentation methods are presented in this framework. Idris et al [42] are dealing with image and video indexation. Image features and video processing algorithms useful for indexation are described.…”

Section: Related Workmentioning

confidence: 99%

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A review of real-time segmentation of uncompressed video sequences for content-based search and retrieval

2003

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We present in this paper a review of methods for segmentation of uncompressed video sequences. Video segmentation is usually performed in the temporal domain by shot change detection. In case of real-time segmentation, computational complexity is one of the criteria which has to be taken into account when comparing different methods. When dealing with uncompressed video sequences, this criterion is even more significant. However previous published reviews did not involve complexity criterion when comparing shot change detection methods. Only recognition rate and ability to classify detected shot changes were considered. So contrary to previous reviews we give here complexity of most of the described methods. We review in this paper an extensive set of methods presented in the literature and classify them in several parts, depending on the information used to detect shot changes. The earliest methods were comparing successive frames by relying on most simple elements, that is to say pixels. Comparison could be performed on a global level, so methods based on histograms were also proposed. Block-based methods have been considered to process data at an intermediate level, between local (using pixels) and global (using histograms) levels. More complex features can be involved, resulting in feature-based methods. Alternatively some methods rely on motion as a criterion to detect shot changes. Finally different kinds of information could be combined together in order to increase the quality of shot change detection. So our review will detail segmentation methods

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Section: Related Workmentioning

confidence: 99%

“…The number of shot change detection methods is now important and several reviews of these methods have been done [3,42,17,7,48,57,44,14,56,22,88,31,32,59]. These reviews often present the different methods and their efficiency based on some quality measures.…”

Section: Introductionmentioning

confidence: 99%

A review of real-time segmentation of uncompressed video sequences for content-based search and retrieval

2003

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“…Suppose a mobile robot equipped with a camera which is moving about an area in a way that is able to take images of the environment and associate them to a pose p consisting in a position (x, y) ∈ R 2 and an orientation θ ∈ [0, 2π), expressed in a chosen framework O.…”

Section: Introductionmentioning

confidence: 99%

A Color Constancy Algorithm for the Robust Description of Images Collected from a Mobile Robot

Vergés-Llahí

Sanfeliu

2004

Lecture Notes in Computer Science

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Abstract. In mobile robotics, it is necessary to have a robust and efficient way of describing the visual stream provided by a vision system to be used afterwards in tasks such as object recognition. Color histograms are a useful tool to capture and represent color properties of sets of images taken from a certain position. Since those images were obtained at different time and light conditions, their appearance have greatly changed, reducing the performance of the color descriptor. In this work, we develop a color constancy algorithm that copes with the color variation among sets of images taken from nearly the same place. We show that the performance of the color histogram descriptor rises after color constancy, becoming a more robust and useful color descriptor. In the results section, we support that claim with several sets of images of scenes belonging to different positions.

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“…The first stage of this process is the initial partitioning (segmentation) of the video data into its constituent scenes and the identification of the various editing effects in the video [3,18]. The next stage involves the analysis of the individual scenes to provide further information for finegrained access to the digital video.…”

Section: Introductionmentioning

confidence: 99%

A Distance Measure for Video Sequences

Adjeroh¹,

Lee²,

King³

1999

Computer Vision and Image Understanding

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Video is a unique multimedia data type, in that it comes with distinguished spatio-temporal constraints. Content-based video retrieval thus requires methods for video sequence-to-sequence matching, incorporating the temporal ordering inherent in a video sequence, without losing sight of the visual nature of the information in the sequence. Such methods will require reliable measures of similarity between the video sequences. In this paper, we formulate the problem of video sequence-to-sequence matching as a patternmatching problem and propose the vstring edit distance as a suitable distance measure for video sequences.

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Review of Image and Video Indexing Techniques

Cited by 216 publications

References 88 publications

A review of real-time segmentation of uncompressed video sequences for content-based search and retrieval

A review of real-time segmentation of uncompressed video sequences for content-based search and retrieval

A Color Constancy Algorithm for the Robust Description of Images Collected from a Mobile Robot

A Distance Measure for Video Sequences

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