A Two-Stage Template Approach to Person Detection in Thermal Imagery

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How researchers see this paper

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Thermal cameras and applications: a survey (2013, methodology): “detection systems are proposed in [81,36,38,174].”
People detection and tracking from aerial thermal views (2014, background): “1 shows intermediate steps within our tracking pipeline when operating on both frontal and oblique views of humans present in our manually annotated and publicly available dataset.”
Long-Term Occupancy Analysis Using Graph-Based Optimisation in Thermal Imagery (2013, methodology): “Examples of systems combining thermal and RGB cameras are given by Davis et al. [9, 11] and Leykin et al. [23, 24].”
Human Body Detection and Geolocalization for UAV Search and Rescue Missions Using Color and Thermal Imagery (2008, methodology): “An approach which ﬁrst performs a fast screening procedure us-ing a template to locate potential person locations, which is then tested using an AdaBoosted ensemble classiﬁer using automatically tuned ﬁlters has been proposed [6].”
RGB-T Object Tracking: Benchmark and Baseline (2018, background): “Thermal datasets [24– 27] only include thermal videos, and their weakness are revealed when thermal crossover occurs.”
Getting to Know Low-light Images with The Exclusively Dark Dataset (2018, methodology): “Common object detection is not usually addressed in surveillance works, although the closest would be face recognition ([20], [21]) and pedestrian detection ([22], [23], [24], [25], [26]).”