Real time face recognition using decision fusion of neural classifiers in the visible and thermal infrared spectrum

Real-time pedestrian detection is a key technology for video surveillance. A widespread approach for detecting pedestrians is the use of color information. In recent times, the use of thermal infrared cameras has revealed to be an excellent alternative that offers good results in people segmentation. Nonetheless, thermal infrared cameras are very sensitive to the overall heat detected at each image. Moreover, a great amount of infrared images has low spatial resolution and lower sensitivity than visible spectrum images due to the technological limitations of infrared cameras. This chapter introduces a comparison of three different algorithms for real-time and robust pedestrian detection in the infrared spectrum. The aim of the paper is to look for the best algorithms prepared to resolve the conflicts that arise in the detection process in image sequences. We propose to use simple rules as conflict resolution mechanism when the outputs of the three algorithms do not coincide.

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Illumination-invariant face recognition from a single image across extreme pose using a dual dimension AAM ensemble in the thermal infrared spectrum

The 2013 International Joint Conference on Neural Networks (IJCNN) ◽

10.1109/ijcnn.2013.6707095 ◽

2013 ◽

Cited By ~ 7

Author(s):

Reza Shoja Ghiass ◽

Ognjen Arandjelovic ◽

Hakim Bendada ◽

Xavier Maldague

Keyword(s):

Face Recognition ◽

Infrared Spectrum ◽

Thermal Infrared ◽

Single Image ◽

Illumination Invariant

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Physiology-Based Face Recognition in the Thermal Infrared Spectrum

Biomedical Signals, Imaging, and Informatics ◽

10.1201/b15468-47 ◽

2014 ◽

pp. 973-988

Keyword(s):

Face Recognition ◽

Infrared Spectrum ◽

Thermal Infrared

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Enhanced Real-Time RGB-T Tracking by Complementary Learners

Journal of Circuits System and Computers ◽

10.1142/s0218126621503072 ◽

2021 ◽

Vol 30 (10) ◽

pp. 2150307

Author(s):

Qingyu Xu ◽

Yangliu Kuai ◽

Junggang Yang ◽

Xinpu Deng

Keyword(s):

Object Tracking ◽

Real Time ◽

High Performance ◽

High Efficiency ◽

Thermal Infrared ◽

Decision Fusion ◽

Correlation Filter ◽

Superior Performance ◽

Fusion Tracking

This paper focuses on integrating information from RGB and thermal infrared modalities to perform RGB-T object tracking in the correlation filter framework. Our baseline tracker is Staple (Sum of Template and Pixel-wise LEarners), which combines complementary cues in the correlation filter framework with high efficiency. Given the input RGB and thermal videos, we utilize the baseline tracker due to its high performance in both of accuracy and speed. Different from previous correlation filter-based methods, we perform the fusion tracking at both the pixel-fusion and decision-fusion levels. Our tracker is robust to the dataset challenges, and due to the efficiency of FFT, our tracker can maintain high efficiency with superior performance. Extensive experiments on the RGBT234 dataset have demonstrated the effectiveness of our work.

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Real Time Person Recognition and Attendance Marking Using Holistic Based Approach

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse/v7i7/0220 ◽

2017 ◽

Vol 7 (7) ◽

pp. 302

Author(s):

Reshma P ◽

Muneer VK ◽

Muhammed Ilyas P

Keyword(s):

Face Recognition ◽

Real Time ◽

High Accuracy ◽

Efficient Technique ◽

Human Face ◽

Traditional Methods ◽

Person Recognition ◽

The Face

Face recognition is a challenging task for the researches. It is very useful for personal verification and recognition and also it is very difficult to implement due to all different situation that a human face can be found. This system makes use of the face recognition approach for the computerized attendance marking of students or employees in the room environment without lectures intervention or the employee. This system is very efficient and requires very less maintenance compared to the traditional methods. Among existing methods PCA is the most efficient technique. In this project Holistic based approach is adapted. The system is implemented using MATLAB and provides high accuracy.

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