Extracting spatio-temporally consistent segments from a video sequence is a challenging problem due to the complexity of color, motion and occlusions. Most existing spatio-temporal segmentation approaches rely on pairwise motion estimation, which have inherent difficulties in handling large displacement with significant occlusions. This paper presents a novel spatio-temporal segmentation method...

Indexing and query processing is an emerging research field in spatio temporal data. Most of the real-time applications such as location based services, fleet management, traffic prediction and radio frequency identification and sensor networks are based on spatiotemporal indexing and query processing. All the indexing and query processing applications is any one of the forms, such as spatio in...

In the geometric data model for spatio-temporal data, introduced by Chomicki and Revesz [1], spatio-temporal data are modelled as a finite collection of triangles that are transformed by time-dependent affinities of the plane. To facilitate querying and animation of spatio-temporal data, we present a normal form for data in the geometric data model. We propose an algorithm for constructing this...

In this paper, we aim to develop a framework for continuous query processing in spatio-temporal databases. The proposed framework distinguishes itself from other query processors by employing two main paradigms: (1) Scalability in terms of the number of concurrent continuous spatio-temporal queries. (2) Incremental evaluation of continuous spatio-temporal queries. Scalability is achieved thorou...

We investigate the capacity of a type of discrete-time recurrent neural network, called timedelay recurrent neural network, for storing spatio-temporal sequences. By introducing the order of a spatio-temporal sequence, the match law between a time-delay recurrent neural network and a spatio-temporal sequence has been established. It has been proved that the full order time-delay recurrent neura...

Recently, several researchers have proposed using spatio-temporal filters for image motion analysis. For example, the optical flow field can be calculated from the output of a set of spatio-temporal filters. Some of the most popular spatio-temporal filters are the space-time Gabor filters, obtained by convolving a time varying image with a space-time Gabor function. Based on the cellular neural...

Knowledge discovery from satellite images in spatio-temporal context remains one of the major challenges in the remote sensing field. It is, always, difficult for a user to manually extract useful information especially when processing a large collection of satellite images. Thus, we need to use automatic knowledge discovery in order to develop intelligent image interpretation systems. In this ...

Local image features or interest points provide compact and abstract representations of patterns in an image. In this paper, we propose to extend the notion of spatial interest points into the spatio-temporal domain and show how the resulting features often reflect interesting events that can be used for a compact representation of video data as well as for its interpretation. To detect spatio-...

The generic framework for monitoring continuous spatial queries over moving objects addresses the location update issue and provides a common interface for monitoring mixed types of queries. It significantly reduces the wireless communication and query reevaluation costs required to maintain the up to-date query results. The papers suggest about the new algorithms and models to evaluate continu...

Thus far, the success of capturing and classifying temporal information with neural networks has been limited. Our methodology adds a spatio-temporal coupling to the Self-Organized Feature Map (SOFM) which creates temporally and spatially localized neighborhoods in the map. The spatio-temporal coupling is based on traveling waves of activity starting at each winning node which are naturally att...