KEYWORDS: Video, Visualization, Image segmentation, Semantic video, Video surveillance, Data storage, RGB color model, Visual process modeling, Convolution, Video processing
In this work, we aim to address the needs of human analysts to consume and exploit data given the proliferation of overhead imaging sensors. We have investigated automatic captioning methods capable of describing and summarizing scenes and activities by providing textual descriptions using natural language for overhead full motion video (FMV). We have integrated methods to provide three types of outputs: (1) summaries of short video clips; (2) semantic maps, where each pixel is labeled with a semantic category; and (3) dense object description to capture object attributes and activities. We show results obtained from VIRAT and Aeroscapes publicly available datasets.
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