Gigapixel videography, beyond the resolution of single camera and human visual perception, plays an important role in capturing large-scale dynamic scene with extremely high resolution for both macro and micro domains. Restricted by the spatial-temporal bandwidth product of optical system, the size, weight, power and cost are central challenges in gigapixel video.
The UnstructureCam we designed, an end-to-end unstructured multi-scale camera system, shows the ability of real-time capture, dynamically adjusting local-view cameras, and online warping for synthesizing gigapixel video. We take the advantage of our UnstructureCam to develop the Gigapixel Video Dataset. And these datasets we provide in www.gigacamera.com are all characterized by extremely high resolution, large scale, wide FOV and huge data throughout. We hope that our datasets will help researchers solve the corresponding computer vision tasks.
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Fig.1: Illustration of representative imaging systems. (a) single camera imaging system faces the contradiction between wide FOV and high resolution, (b) single-scale camera array imaging  relies on image stitching, (c) structured multi-scale camera array (AWARE2) adopts two-stage optical imaging design, (d) un-structured multi-scale camera array (denoted as UnstructureCam).