We now live in a world that can be thought of a massive heterogeneous visual sensor network with devices ranging from first-person vision systems to unmanned aerial imaging platforms capable of sensing the world around us from wildly different perspectives. The images captured from these different perspectives are complementary, and so fusing them is a logical approach for improving vision-based object and event understanding. For example, while a wearable camera mounted on a subject can capture an event closely and in great detail, an aerial imaging system observing the event from above can provide the geospatial context necessary to interpret the event. The key to integrating these different perspectives—to get them to converge—is, of course, location. We feel that due to the growing availability of geo-referenced images and videos, the time is right to investigate the research challenges and opportunities involved with jointly analyzing images and videos captured from different devices and from wildly varying perspectives but of the same location. Combining this heterogeneous visual data could lead to improved data organization strategies, event understanding systems, and transformative solutions for computer vision challenges. The focus of this workshop therefore is to explore techniques that can exploit the rich data provided by converging perspectives, such as first-person cameras, street view sensors, mobile phones, and aerial images.