Introduction Most fMRI data display significant higher-order statistics representing tendencies to grouping along various shapes, even if such feature is commonly hidden by the overall distribution. Since the spatiotemporal characteristics of brain activity are frequently unknown and variable, their evaluation using hypothesis-driven methods only is rather difficult. Analysis of an fMRI block-b...

Urbanization is arguably the most dramatic form of highly irreversible land transformation. While urbanization is a worldwide phenomenon, it is exceptionally dynamic in India, where unprecedented urban growth rates have occurred over the last 30 years. In this uncontrolled explosive situation city planning lacks of data and information to measure, monitor, understand urban sprawl processes. The...

The large-scale images and videos are one kind of the main source of big data. Dynamic texture (DT) is essential for understanding the video sequences with spatio-temporal similarities. This paper presents a powerful tool called dynamic fractal analysis to DT description and classification, which integrates rich description of DT with strong robustness to environmental changes. The proposed dyn...

This paper describes a method for recognizing and measuring the motion of each individual leukocyte in microvessels from a sequence of images. A spatiotemporal image is generated whose spatial axes are parallel and vertical to vessel region contours. In order to enhance and extract only leukocyte traces with a tuned velocity range even under noisy background, we use a combination of a ltering p...

For multilevel data, levels are not the result of a hierarchical aggregation, but contain independently produced data. While first visualization techniques for this kind of data exist, suitable interactive exploration techniques have rarely been investigated so far. In this paper, we introduce means for the analysis, representation, and exploration of spatiotemporal multilevel data as first sol...

Previous methods for analyzing optical imaging data have relied heavily on temporal averaging. However, response dynamics are rich sources of information. Here, we develop and present a method that combines principal component analysis and multitaper harmonic analysis to extract the statistically significant spatial and temporal response from optical imaging data. We apply the method to both si...

3. DEFINITION Spatio-temporal social networks model the relationships expressed in a social network and the changes to it over time. These changes can be of two types; First, Changes to the level of expressed relationship between two or more actors. For example, in a social network which expresses trust, there could be a change in the level of trust between two actors. Second, changes to the ph...

In this paper we propose a novel feature extracting method based on spatiotemporal slice analyzing. To date, video features are focused on the character of every single video frame. With our method, the video content is no longer represented with every single frame. The temporal variation of visual information is taken as an important feature of video in our method. We examined this kind of fea...

An abundance of information on earth resources is being collected daily such as remotely sensed imagery, Global Positioning System (GPS) surveys, aerial photographs and ground truth data. Interpreted by resource experts and compiled into geographic information system (GIS) digital databases, these data are increasingly available for viewing and distribution over the world wide web. With such a ...