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W. Ketchantang, S. Derrode, S. Bourennane, L. Martin's Advanced Concepts for Intelligent Vision Systems: 7th PDF

By W. Ketchantang, S. Derrode, S. Bourennane, L. Martin (auth.), Jacques Blanc-Talon, Wilfried Philips, Dan Popescu, Paul Scheunders (eds.)

ISBN-10: 354029032X

ISBN-13: 9783540290322

This publication constitutes the refereed lawsuits of the seventh foreign convention on complex ideas for clever imaginative and prescient platforms, ACIVS 2005, held in Antwerp, Belgium in September 2005.

The ninety revised complete papers awarded have been conscientiously reviewed and chosen from round two hundred submissions. The papers are equipped in topical sections on biometrics, type and popularity, content material and function characterization, photo and video research, photo and video coding, photograph and video segmentation, clinical photo processing purposes, movement estimation and monitoring, noise relief and restauration, and real-time processing and hardware.

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Read Online or Download Advanced Concepts for Intelligent Vision Systems: 7th International Conference, ACIVS 2005, Antwerp, Belgium, September 20-23, 2005. Proceedings PDF

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Extra info for Advanced Concepts for Intelligent Vision Systems: 7th International Conference, ACIVS 2005, Antwerp, Belgium, September 20-23, 2005. Proceedings

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4 layers, 447 connections, with 24 × 24 pixels as inputs, two hidden layers (2 × 2 and 8 × 8 neurons), each unit locally connected to a sub-block from its adjacent lower layer. 4 layers, 2039 connections, enhanced version of FNET-B and FNETC, with additional hidden neurons arranged in horizontal and vertical stripes. 4 layers, 3459 connections, enhanced version of FNET-D allowing overlapping of locally connected blocks. Detection Accuracy. , αL ) < Td }, (2) where Td is a threshold for the final false acceptance rate.

In our method, the filtered image does sometimes still contain some parts of background objects (Figure 1b); this is because we use a relatively simple method. The development of a general method for background subtraction is a challenging task [5][9]. a) d) g) b) c) e) h) f) i) Fig. 1. Overview of pattern-extraction: a) Image from input sequence. b) Result of changedetection. c) Filtered Canny edge-map. d) First level symmetries. e) Second level symmetries. f) Third-level symmetries (L3S). g) Reconstructed masks from symmetries.

1 Background Subtraction An elementary method to reduce the computation cost of methods using motion information derived from static-position cameras is that of background subtraction (or change-detection). In our method, the filtered image does sometimes still contain some parts of background objects (Figure 1b); this is because we use a relatively simple method. The development of a general method for background subtraction is a challenging task [5][9]. a) d) g) b) c) e) h) f) i) Fig. 1. Overview of pattern-extraction: a) Image from input sequence.

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Advanced Concepts for Intelligent Vision Systems: 7th International Conference, ACIVS 2005, Antwerp, Belgium, September 20-23, 2005. Proceedings by W. Ketchantang, S. Derrode, S. Bourennane, L. Martin (auth.), Jacques Blanc-Talon, Wilfried Philips, Dan Popescu, Paul Scheunders (eds.)


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