On improving eye feature extraction using deformable templates

Xie, Xangdong; Sudhakar, R.; Zhuang, Hanqi

doi:10.1016/0031-3203(94)90164-3

Cited by 116 publications

(54 citation statements)

References 6 publications

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“…The approach presented in this paper is based on Deformable Templates [1], [10], [11], [15], [6], [28], [29], [30], [31], [20], [26]. In the context of intravascular ultrasound imaging we introduce improvements mainly in two directions: 2.…”

Section: The Proposed Approach: Outline Of the Papermentioning

confidence: 99%

Deformable templates for tracking and analysis of intravascular ultrasound sequences

Escolano

Cazorla

Gallardo

et al. 1997

Lecture Notes in Computer Science

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Section: The Proposed Approach: Outline Of the Papermentioning

confidence: 99%

Deformable templates for tracking and analysis of intravascular ultrasound sequences

Escolano

Cazorla

Gallardo

et al. 1997

Lecture Notes in Computer Science

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“…In the template-based methods, a generic eye model is first designed and the template matching is used to detect the eyes on the image. The deformable template method is a commonly used template based method [6][7][8]. In this method, an eye model is first designed and then the eye position is obtained via a recursive process.…”

Section: Introductionmentioning

confidence: 99%

An FPGA-based Parallel Hardware Architecture for Real-time Eye Detection

Kim¹,

Jung²,

Nguyen³

et al. 2012

JSTS:Journal of Semiconductor Technology and Science

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Abstract-Eye detection is widely used in applications, such as face recognition, driver behavior analysis, and human-computer interaction. However, it is difficult to achieve real-time performance with software-based eye detection in an embedded environment. In this paper, we propose a parallel hardware architecture for real-time eye detection. We use the AdaBoost algorithm with modified census transform(MCT) to detect eyes on a face image. We parallelize part of the algorithm to speed up processing. Several downscaled pyramid images of the eye candidate region are generated in parallel using the input face image. We can detect the left and the right eye simultaneously using these downscaled images. The sequential data processing bottleneck caused by repetitive operation is removed by employing a pipelined parallel architecture. The proposed architecture is designed using Verilog HDL and implemented on a Virtex-5 FPGA for prototyping and evaluation. The proposed system can detect eyes within 0.15 ms in a VGA image.

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“…The template is matched with the input image by minimizing an energy function. Later, Xie et al [5] improved further the eye deformable template by including extra terms in the energy function used to determine the parameters of the template. Often, these template matching techniques do not produce accurate results, and they are quite sensitive to the initial parameters of the eye template [6].…”

Section: Introductionmentioning

confidence: 99%

A fast neural-based eye detection system

Tivive

Bouzerdoum

2005

2005 International Symposium on Intelligent Signal Processing and Communication Systems

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This paper presents a fast eye detection system which is based on an artificial neural network known as the shunting inhibitory convolutional neural network, or SICoNNet for short. With its two-dimensional network architecture and the use of convolution operators, the eye detection system processes an entire input image and generates the location map of the detected eyes at the output. The network consists of 479 trainable parameters which are adapted by a modified Levenberg-Marquardt training algorithm in conjunction with a bootstrap procedure. Tested on 180 real images, with 186 faces, the accuracy of the eye detector reaches 96.8% with only 38 false detections. Disciplines Physical Sciences and Mathematics Publication DetailsThis article was originally published as:

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On improving eye feature extraction using deformable templates

Cited by 116 publications

References 6 publications

Deformable templates for tracking and analysis of intravascular ultrasound sequences

Deformable templates for tracking and analysis of intravascular ultrasound sequences

An FPGA-based Parallel Hardware Architecture for Real-time Eye Detection

A fast neural-based eye detection system

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