Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Computational Intelligence in Multi-Feature Visual Pattern Recognition: Hand Posture and Face Recognition Using Biologically Inspired Approaches

Computational Intelligence in Multi-Feature Visual Pattern Recognition: Hand Posture and Face Recognition Using Biologically Inspired Approaches

Pisharady, Pramod Kumar
Poh, Loh Ai
Vadakkepat, Prahlad

Paperback

Series: Studies in Computational Intelligence, Book 556

Technology & EngineeringGeneral ComputersProgramming

ISBN10: 9811011710
ISBN13: 9789811011719
Publisher: Springer Nature
Published: Sep 27 2016
Pages: 138
Weight: 0.50
Height: 0.33 Width: 6.14 Depth: 9.21
Language: English

This book presents a collection of computational intelligence algorithms that addresses issues in visual pattern recognition such as high computational complexity, abundance of pattern features, sensitivity to size and shape variations and poor performance against complex backgrounds. The book has 3 parts. Part 1 describes various research issues in the field with a survey of the related literature. Part 2 presents computational intelligence based algorithms for feature selection and classification. The algorithms are discriminative and fast. The main application area considered is hand posture recognition. The book also discusses utility of these algorithms in other visual as well as non-visual pattern recognition tasks including face recognition, general object recognition and cancer / tumor classification. Part 3 presents biologically inspired algorithms for feature extraction. The visual cortex model based features discussed have invariance with respect to appearance and size of the hand, and provide good inter class discrimination. A Bayesian model of visual attention is described which is effective in handling complex background problem in hand posture recognition.

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