Human Detection in Static Images

Human Detection in Static Images

Hui-Xing Jia (Tsinghua University - Beijing, China) and Yu-Jin Zhang (Tsinghua University - Beijing, China)
Copyright: © 2008 |Pages: 17
DOI: 10.4018/978-1-59904-807-9.ch010
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Abstract

Human detection is the first step for a number of applications such as smart video surveillance, driving assistance systems, and intelligent digital content management. It’s a challenging problem due to the variance of illumination, color, scale, pose, and so forth. This chapter reviews various aspects of human detection in static images and focuses on learning-based methods that build classifiers using training samples. There are usually three modules for these methods: feature extraction, classifier design, and merge of overlapping detections. The chapter reviews most existing methods for each module and analyzes their respective pros and cons. The contribution includes two aspects: first, the performance of existing feature sets on human detection are compared; second, a fast human detection system based on histogram of oriented gradients features and cascaded AdaBoost classifier is proposed. This chapter should be useful for both algorithm researchers and system designers in the computer vision and pattern recognition community.

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Table of Contents
Preface
Brijesh Verma, Michael Blumenstein
Acknowledgment
Brijesh Verma, Michael Blumenstein
Chapter 1
Brijesh Verma, Michael Blumenstein
Cursive handwriting recognition is a challenging task for many real-world applications such as document authentication, form processing, postal... Sample PDF
Fusion of Segmentation Strategies for Off-Line Cursive Handwriting Recognition
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Chapter 2
Seiichi Uchida
This chapter reviews various elastic matching techniques for handwritten character recognition. Elastic matching is formulated as an optimization... Sample PDF
Elastic Matching Techniques for Handwritten Character Recognition
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Chapter 3
Luana Batista, Dominique Rivard, Robert Sabourin, Eric Granger, Patrick Maupin
Automatic signature verification is a biometric method that can be applied in all situations where handwritten signatures are used, such as cashing... Sample PDF
State of the Art in Off-Line Signature Verification
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Chapter 4
Vamsi Krishna Madasu, Brian C. Lovell
This chapter presents an off-line signature verification and forgery detection system based on fuzzy modeling. The various handwritten signature... Sample PDF
An Automatic Off-Line Signature Verification and Forgery Detection System
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Chapter 5
Sergio Suárez-Guerra, Jose Luis Oropeza-Rodriguez
This chapter presents the state-of-the-art automatic speech recognition (ASR) technology, which is a very successful technology in the computer... Sample PDF
Introduction to Speech Recognition
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Chapter 6
Graham Leedham, Vladimir Pervouchine, Haishan Zhong
This chapter examines features of handwriting and speech and their effectiveness at determining whether the identity of a writer or speaker can be... Sample PDF
Seeking Patterns in the Forensic Analysis of Handwriting and Speech
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Chapter 7
Donggang Yu, Tuan D. Pham
This chapter describes a new pattern recognition method: pattern recognition-based morphological structure. First, smooth following and... Sample PDF
Image Pattern Recognition-Based Morphological Structure and Applications
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Chapter 8
Ting Shan, Abbas Bigdeli, Brian C. Lovell, Shaokang Chen
In this chapter, we propose a pose variability compensation technique, which synthesizes realistic frontal face images from nonfrontal views. It is... Sample PDF
Robust Face Recognition Technique for a Real-Time Embedded Face Recognition System
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Chapter 9
Prithwijit Guha, Amitabha Mukerjee, K. S. Venkatesh
Complex multiobject interactions result in occlusion sequences, which are a visual signature for the event. In this work, multiobject interactions... Sample PDF
Occlusion Sequence Mining for Activity Discovery from Surveillance Videos
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Chapter 10
Hui-Xing Jia, Yu-Jin Zhang
Human detection is the first step for a number of applications such as smart video surveillance, driving assistance systems, and intelligent digital... Sample PDF
Human Detection in Static Images
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Chapter 11
Fok Hing Chi Tivive, Abdesselam Bouzerdoum
With the ever-increasing utilization of imagery in scientific, industrial, civilian, and military applications, visual pattern recognition has been... Sample PDF
A Brain-Inspired Visual Pattern Recognition Architecture and Its Applications
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Chapter 12
Mariusz Rawski, Henry Selvaraj, Bogdan J. Falkowski, Tadeusz Luba
This chapter, taking FIR filters as an example, presents the discussion on efficiency of different implementation methodologies of DSP algorithms... Sample PDF
Significance of Logic Synthesis in FPGA-Based Design of Image and Signal Processing Systems
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Chapter 13
Nina Zhou, Lipo Wang
This chapter introduces an approach to class-dependent feature selection and a novel support vector machine (SVM). The relative background and... Sample PDF
A Novel Support Vector Machine with Class-Dependent Features for Biomedical Data
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Chapter 14
Alistair Shilton, Marimuthu Palaniswami
This chapter presents a unified introduction to support vector machine (SVM) methods for binary classification, one-class classification, and... Sample PDF
A Unified Approach to Support Vector Machines
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Chapter 15
Katti Faceli, Andre C.P.L.F. de Carvalho, Marcilio C.P. de Souto
Clustering is an important tool for data exploration. Several clustering algorithms exist, and new algorithms are frequently proposed in the... Sample PDF
Cluster Ensemble and Multi-Objective Clustering Methods
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Chapter 16
Peter Duell, Xin Yao
Negative correlation learning (NCL) is a technique that attempts to create an ensemble of neural networks whose outputs are accurate but negatively... Sample PDF
Implementing Negative Correlation Learning in Evolutionary Ensembles with Suitable Speciation Techniques
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Chapter 17
Toshio Tsuji, Nan Bu, Osamu Fukuda
In the field of pattern recognition, probabilistic neural networks (PNNs) have been proven as an important classifier. For pattern recognition of... Sample PDF
A Recurrent Probabilistic Neural Network for EMG Pattern Recognition
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