Human Detection in IR

Many human detection algorithms are able to detect humans in various environmental conditions with high accuracy, but they lack the ability to give the exact region of where the human is located (usual detections as a bounding box). Our algorithm uses gradient information through the Histogram of Oriented Gradients and texture information through the center-symmetric local binary pattern. Various binning strategies help keep the inherent structure embedded in the features, which provide enough information for robust detection of the humans in the scene. Our algorithm is shown to create a better representation of the human detection in infrared imagery for analysis of scenes as compared to normal detection strategies.

HOP: Histogram of Oriented Phase

HOG: Histogram of Oriented Gradient

CSLBP: Central Symmetric Local Binary Pattern

FPGT: Fused Phase, Gradient and Texture Features

Publications

Hussin Ragb and Vijayan K. Asari, "Multi-feature fusion for robust human detection in thermal infrared imagery," SPIE Journal of Optical Engineering, doi.org/10.1117/1.OE.58.4.043101, vol. 58, no. 4, pp. 043101: 1-10, April 2019.
Hussin Ragb, Theus Aspiras, and Vijayan K. Asari, "Human detection in infrared imagery using gradient and texture features and super-pixel segmentation," IEEE International Conference on Technologies for Homeland Security (IEEE HST 2018), Woburn, Massachusetts, USA, 23-24 October 2018.
Hussin K. Ragb, Vijayan K. Asari, and Theus H. Aspiras, "Human detection in infrared imagery using intensity distribution, gradient and texture features," Proceedings of the SPIE Defense + Commercial Sensing: Mobile Multimedia/Image Processing, Security, and Applications 2018 (Multimedia Algorithms and Systems) , Orlando, Florida, United States, vol. 10668, pp. 1-8, 15 - 19 April 2018.
Hussin Ragb, Theus Aspiras, and Vijayan K. Asari, "Depth and super-pixel extraction for augmenting human detection," Proceedings of the IS&T International Symposium on Electronic Imaging: Imaging and Multimedia Analytics in a Web and Mobile World , Burlingame, California, USA, pp. 336: 1-6, 28 January - 01 February 2018.
Hussin Ragb and Vijayan K. Asari, "A feature fusion strategy for human detection in omnidirectional camera imagery," Proceedings of the IS&T International Symposium on Electronic Imaging: Imaging and Multimedia Analytics in a Web and Mobile World , Burlingame, California, USA, pp. 375: 1-5, 28 January - 01 February 2018.
Hussin Ragb, Theus Aspiras, Vijayan K. Asari and Pramud Rawat, "Omnidirectional camera image analysis for law-enforcement and border control applications," IEEE International Conference on Technologies for Homeland Security (IEEE HST 2017), Waltham, Massachusetts, USA, 25 -26 April 2017.
Hussin Ragb and Vijayan K. Asari, "Histograms of oriented phase and gradient (HOPG) descriptor for improved pedestrian detection," IS&T International Conference on Electronic Imaging: Video Surveillance and Transportation Imaging Applications 2016, San Francisco, California, USA, 14-18 February 2016.

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