Kristin Eickhorst

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Spatiotemporal helixes are a novel way to model spatiotemporal change. They represent both the movement of an object, as it is expressed by the trajectory of its center, and the changes of its outline. Accordingly they are highly suitable to communicate the evolution of phenomena as they are captured e.g. in sequences of imagery. In this paper we present(More)
Spatiotemporal helixes constitute a novel method we developed for modeling changes in an object over time. Changes in both an object’s trajectory and its outline can be represented with these helixes. In addition, spatiotemporal helixes can be compared to determine whether multiple objects have undergone similar changes. In this paper, we present a method(More)
Current query systems for video databases rely heavily on structured schemas and often require user annotation of data. These systems need to be made more flexible and accessible to the diverse organizations that utilize them. By building on current work with lifelines, and incorporating new structures for organizing metadata, we can make great strides(More)
Video query systems have been used increasingly for both business and personal applications. Many applications for video data involve stationary cameras, resulting in a stable background and moving objects in the foreground. The movements of these objects can be extracted to form lifelines using techniques such as those developed in our lab. Our current(More)
Spatiotemporal helixes are a new method for modeling the changes an object experiences over time. They have the potential to be used as a predictive tool for geographical and biological applications. We present the formal foundations of these helixes and include experiments to demonstrate their usefulness when data collection is not optimal, such as when(More)
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