2018 · 72 citations · 23 references
ComputingVision ScienceComputer VisionMachine VisionSensor FusionObject DetectionObject Detection FusionObject RecognitionVideo AnalysisVisual TrackingMulti-object TrackingThermal Infrared Imaging
We present a visual-infrared video sequence dataset for object detection and tracking, called the CAMEL dataset <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> . The dataset consists of 26 video sequences captured in the visible and thermal infrared domains. The sequences include multiple real world urban environments, as well as multiple targets. The goal is to provide a challenging benchmark similar to MOT challenge that includes sequences that have corresponding visual and infrared pairs. Our hope is that this dataset can be used to help improve work on visible-infrared fusion techniques, as well as object detection and tracking.
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