George Azzopardi, Nicolai Petkov's Computer Analysis of Images and Patterns: 16th International PDF

By George Azzopardi, Nicolai Petkov

ISBN-10: 331923191X

ISBN-13: 9783319231914

ISBN-10: 3319231928

ISBN-13: 9783319231921

The quantity set LNCS 9256 and 9257 constitutes the refereed complaints of the sixteenth foreign convention on machine research of pictures and styles, CAIP 2015, held in Valletta, Malta, in September 2015. The 138 papers awarded have been conscientiously reviewed and chosen from various submissions. CAIP 2015 is the 16th within the CAIP sequence of biennial overseas meetings dedicated to all points of computing device imaginative and prescient, snapshot research and processing, trend attractiveness, and similar fields.

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Detected occludees, denoted by bee kj , are tagged with their occluder track ID. Let j denote the occluder tracker ID, and k the index of the occludee (superscript “ee” for “occludee”). We assume that each occluder has a maximum of two occludees, with k = l if on the left, or k = r if on the right. We adopt again the tracking-by-detection method to track detected occludees. Different to occluders, where we apply detection-by-tracking, occludees are detected by our proposed context-based multiple-cue detector.

In recent years, many approaches have been introduced for uncovering those relationships. The so-called statistical co-occurrence analysis for doing so is a popular means as this technique is very effective and can be easily implemented. Co-occurrences are word pairs that occur together in any order in a predefined window of n words. The most prominent kinds of co-occurrences are word pairs that appear as immediate neighbours or together in a sentence. Word pairs that co-occur with a higher probability than expected stand in a syntagmatic relation [5] to each other and are also known as significant co-occurrences.

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Computer Analysis of Images and Patterns: 16th International Conference, CAIP 2015, Valletta, Malta, September 2-4, 2015 Proceedings, Part I by George Azzopardi, Nicolai Petkov


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