Multimodal Biometrics for Access Control in an Intelligent Car

Lupu, Catalin; Lupu, Valeriu

doi:10.1109/isciii.2007.367399

Cited by 13 publications

(3 citation statements)

References 3 publications

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“…Over the past few years, biometric authentication systems have become highly popular and widespread. They are widely used in such areas as automated teller machines [28], the automotive industry [18], or at check-in points at airports [2]. However, when moving to less-cooperative scenarios where the acquisition conditions are significantly lower and subject cooperation is not acceptable, a huge drop in recognition performance can be observed.…”

Section: Introductionmentioning

confidence: 99%

COMPACT: Biometric Dataset of Face Images Acquired in Uncontrolled Indoor Environment

Włodarczyk

Kacperski

Sankowski

et al. 2019

csci

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Biometric databases are important components that help improve the performance of state-of-the-art recognition applications. The availability of more and more challenging data is attracting the attention of researchers, who are systematically developing novel recognition algorithms and increasing the accuracy of identification. Surprisingly, most of the popular face datasets (like LFW or IJBA) are not fully unconstrained. The majority of the available images were not acquired on-the-move, which reduces the amount of blurring that is caused by motion or incorrect focusing. Therefore, the COMPACT database for studying less-cooperative face recognition is introduced in this paper. The dataset consists of high-resolution images of 108 subjects acquired in a fully automated manner as people go through the recognition gate. This ensures that the collected data contains real-world degradation factors: different distances, expressions, occlusions, pose variations, and motion blur. Additionally, the authors conducted a series of experiments that verified the face-recognition performance on the collected data.

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Section: Introductionmentioning

confidence: 99%

COMPACT: Biometric Dataset of Face Images Acquired in Uncontrolled Indoor Environment

Włodarczyk

Kacperski

Sankowski

et al. 2019

csci

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“…Through detecting and recognizing some particular signs, this kind of robot makes judgment based on these signs, and reaches the destination accurately with the fastest speed. It has been widely used in more and more occasions because of its walking flexibly, recognizing fast, positioning accurately as well as moving quickly [14].…”

Section: Introductionmentioning

confidence: 99%

Design of an Intelligent Car for Searching Track and Avoiding Obstacles

Yang

Liu

2015

International Journal on Smart Sensing and Intelligent Systems

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Abstract-With the rapid development of informational and intelligent technology, the mobile robot has become an important branch of robot. In this paper, through UP-InnoSTARTM robot kits for the chassis and MultiFLEXTM 2-PXA270 controller for the control core, we design an intelligent car. It uses infrared proximity sensors to detect obstacles and gray-scale sensors to search the track. And the main functions are: autonomously recognizing the trajectory, searching it steadily, making quick judgment and timely responses when meeting obstacles. In addition, a simple laboratory experiments are also proposed to illustrate the practicability of our design.

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“…Thirdly, some persons cannot provide the required standalone biometric, owing to illness or disabilities [2]. The multimodal biometric systems provide advantage over the conventional Unimodal biometric systems in various ways, we discuss this in the coming section, summarizing here we put the limitations [3] of Unimodal biometric systems as:…”

Section: Introductionmentioning

confidence: 99%

Multimodal Biometrics it is: Need for Future Systems

Mishra¹

2010

IJCA

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A biometric system is essentially a pattern recognition system that operates by acquiring biometric data from an individual, extracting a feature set from the acquired data, and comparing this feature set against the template set in the database. Multimodal biometric systems are becoming more and more popular, they have more accuracy as compared to unimodal biometric systems. On the other hand these systems are more complex. We discuss here different types of multimodal biometric systems, different decision fusion techniques used in these systems. We discuss their feasibility and advantage over unimodal biometric systems & some of the future directions of biometrics system.

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Multimodal Biometrics for Access Control in an Intelligent Car

Cited by 13 publications

References 3 publications

COMPACT: Biometric Dataset of Face Images Acquired in Uncontrolled Indoor Environment

COMPACT: Biometric Dataset of Face Images Acquired in Uncontrolled Indoor Environment

Design of an Intelligent Car for Searching Track and Avoiding Obstacles

Multimodal Biometrics it is: Need for Future Systems

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