@inproceedings{Doulamis2017a,

title = {Human object detection using very low resolution thermal cameras for urban search and rescue},

author = {Nikolaos Doulamis and Panagiotis Agrafiotis and George Athanasiou and Angelos Amditis},

url = {https://dl.acm.org/doi/10.1145/3056540.3076201},

doi = {10.1145/3056540.3076201},

isbn = {9781450352277},

year  = {2017},

date = {2017-06-01},

booktitle = {ACM Int. Conf. Proceeding Ser.},

volume = {Part F1285},

pages = {311--318},

publisher = {ACM},

address = {New York, NY, USA},

abstract = {In this paper, we propose an innovative assistive system for victims' localization under an Urban Search and Rescue environment. The localization exploits miniaturized Long Wave Infrared (LWIR) cameras and algorithms properly combined with template matching schemes from visual cues. The approach first thresholds the data to roughly estimate alive victims' location and then apply a segmentation scheme to improve the probability analysis. The key challenge of our approach is the fact the thermal image used captures images at very low resolution. This selection is necessary so that the sensor is light and thus able to be carried out by a snake robot. Experiments are presented to demonstrate the efficiency of our results both at the laboratory and under real-life conditions. The latter have been conducted under the aegis of FP7- INACHUS European Union funded project.},

keywords = {LWIR Camera, Search and Rescue, Survivor Detection},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Agrafiotis2016b,

title = {Real time earthquake's survivor detection using a miniaturized LWIR camera},

author = {Panagiotis Agrafiotis and Anastasios Doulamis and George Athanasiou and Angelos Amditis},

url = {http://dl.acm.org/citation.cfm?doid=2910674.2935864},

doi = {10.1145/2910674.2935864},

isbn = {9781450343374},

year  = {2016},

date = {2016-01-01},

booktitle = {ACM Int. Conf. Proceeding Ser.},

volume = {29-June-20},

pages = {1--4},

publisher = {ACM Press},

address = {New York, New York, USA},

abstract = {In this paper a system suitable to perform precise and fast earthquake's survivor detection using a miniaturized Long Wave Infrared (LWIR) camera is described. Main challenge of this work is the detection environment which may be characterized by smoke, dust, rubble and extremely narrow spaces as well as the extremely low resolution of the continuous moving LWIR camera. To this direction the thermal information received by the LWIR camera is exploited. In addition, research is carried out in order to implement feature descriptors for detecting only parts of partly occluded people (arms, etc.) in order to reduce false positive ratio. The proposed system achieves real time earthquake's survivor detection using a miniaturized LWIR camera. The results have been tested and evaluated in real life conditions using two different LWIR cameras for proving the robustness and the accuracy of the developed system.},

keywords = {LWIR Camera, Search and Rescue, Survivor Detection},

pubstate = {published},

tppubtype = {inproceedings}

}