By George Azzopardi, Nicolai Petkov
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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Additional info for Computer Analysis of Images and Patterns: 16th International Conference, CAIP 2015, Valletta, Malta, September 2-4, 2015 Proceedings, Part I
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  to each other and are also known as signiﬁcant co-occurrences.
In: ICCV (2009) 21. : Multiple target tracking based on undirected hierarchical relation hypergraph. In CVPR, 2014 22. : An adaptable time-delay neural-network algorithm for image sequence analysis. IEEE Trans. Neural Networks 10(6), 1531–1536 (1999) 23. : Recognizing proxemics in personal photos. In: CVPR (2012) Correlating Words - Approaches and Applications Mario M. de/kn/en/ Abstract. The determination of characteristic and discriminating terms as well as their semantic relationships plays a vital role in text processing applications.
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