From Camera Array to CrowdCam
Multi camera systems significantly evolved over time and have been used to solve a variety of problems in computer vision. We will consider a particular use of a camera array to recover accurate 3D structure and 3D motion of a dynamic scene. Traditionally, camera arrays are carefully assembled in the lab, and are controlled by a single user - the photographer. But recently the way we capture images changed before our eyes. One can often see a group of people, armed with smartphones, huddling together to take pictures of some exciting dynamic event. The data obtained this way can be regarded as the output of a new type of an ad-hoc camera array, which we call a crowd-based camera (or CrowdCam). Different from traditional camera array, CrowdCam is operated by multiple photographers, and there is no single moment of capture. Moreover, the data obtained by CrowdCam lacks accurate temporal information since the cameras cannot be assumed to be calibrated or synchronized. We are interested in developing tools that analyze, explore and visualize CrowdCamimages and a first step in this direction is to recover the temporal order of the images. We term this problem photo sequencing and present a geometry-based solution to it. Finally, future applications and following challenges will be presented.