scholarly journals A Signature-based Video Indexing Scheme using Spatio-Temporal Modeling for Content-based and Concept-based Retrieval on Moving Objects

2002 ◽  
Vol 9D (1) ◽  
pp. 31-42
Author(s):  
Chun-Bo Sim ◽  
Jae-U Jang
Keyword(s):  
Moving Objects ◽  
Video Indexing ◽  
Temporal Modeling ◽  
Indexing Scheme ◽  
Spatio Temporal

scholarly journals Pyramidal Framework: Guidance for the Next Generation of GIS Spatial-Temporal Models

2021 ◽  
Vol 10 (3) ◽  
pp. 188
Author(s):  
Cyril Carré ◽  
Younes Hamdani
Keyword(s):  
Conceptual Models ◽  
Future Generations ◽  
Temporal Data ◽  
Temporal Modeling ◽  
Temporal Models ◽  
Gis Data ◽  
Spatio Temporal ◽  
New Interpretation ◽  
Conventional Literature

Over the last decade, innovative computer technologies and the multiplication of geospatial data acquisition solutions have transformed the geographic information systems (GIS) landscape and opened up new opportunities to close the gap between GIS and the dynamics of geographic phenomena. There is a demand to further develop spatio-temporal conceptual models to comprehensively represent the nature of the evolution of geographic objects. The latter involves a set of considerations like those related to managing changes and object identities, modeling possible causal relations, and integrating multiple interpretations. While conventional literature generally presents these concepts separately and rarely approaches them from a holistic perspective, they are in fact interrelated. Therefore, we believe that the semantics of modeling would be improved by considering these concepts jointly. In this work, we propose to represent these interrelationships in the form of a hierarchical pyramidal framework and to further explore this set of concepts. The objective of this framework is to provide a guideline to orient the design of future generations of GIS data models, enabling them to achieve a better representation of available spatio-temporal data. In addition, this framework aims at providing keys for a new interpretation and classification of spatio-temporal conceptual models. This work can be beneficial for researchers, students, and developers interested in advanced spatio-temporal modeling.

scholarly journals Extracting Stops from Spatio-Temporal Trajectories within Dynamic Contextual Features

2021 ◽  
Vol 13 (2) ◽  
pp. 690
Author(s):  
Tao Wu ◽  
Huiqing Shen ◽  
Jianxin Qin ◽  
Longgang Xiang
Keyword(s):  
Moving Objects ◽  
Major Effect ◽  
Location Based Services ◽  
Trajectory Data ◽  
The Road ◽  
Contextual Features ◽  
Novel Approach ◽  
Gps Trajectories ◽  
Time Distance ◽  
Spatio Temporal

Identifying stops from GPS trajectories is one of the main concerns in the study of moving objects and has a major effect on a wide variety of location-based services and applications. Although the spatial and non-spatial characteristics of trajectories have been widely investigated for the identification of stops, few studies have concentrated on the impacts of the contextual features, which are also connected to the road network and nearby Points of Interest (POIs). In order to obtain more precise stop information from moving objects, this paper proposes and implements a novel approach that represents a spatio-temproal dynamics relationship between stopping behaviors and geospatial elements to detect stops. The relationship between the candidate stops based on the standard time–distance threshold approach and the surrounding environmental elements are integrated in a complex way (the mobility context cube) to extract stop features and precisely derive stops using the classifier classification. The methodology presented is designed to reduce the error rate of detection of stops in the work of trajectory data mining. It turns out that 26 features can contribute to recognizing stop behaviors from trajectory data. Additionally, experiments on a real-world trajectory dataset further demonstrate the effectiveness of the proposed approach in improving the accuracy of identifying stops from trajectories.

Spatio-Temporal Modeling on Village Land Feature Change

2012 ◽  
Vol 204-208 ◽  
pp. 2721-2725
Author(s):  
Hua Ji Zhu ◽  
Hua Rui Wu
Keyword(s):  
Real World ◽  
Temporal Change ◽  
End Users ◽  
Temporal Modeling ◽  
The Real ◽  
Change Type ◽  
Feature Change ◽  
Spatio Temporal ◽  
The Village ◽  
Land Changes

Village land continually changes in the real world. In order to keep the data up-to-date, data producers need update the data frequently. When the village land data are updated, the update information must be dispensed to the end-users to keep their client-databases current. In the real world, village land changes in many forms. Identifying the change type of village land (i.e. captures the semantics of change) and representing them in the data world can help end-users understand the change commonly and be convenient for end-users to integrate these change information into their databases. This work focuses on the model of the spatio-temporal change. A three-tuple model CAR for representing the spatio-temporal change is proposed based on the village land feature set before change and the village land feature set after change, change type and rules. In this model, the C denotes the change type. A denotes the attribute set; R denotes the judging rules of change type. The rule is described by the IF－THEN expressions. By the operations between R and A, the C is distinguished. This model overcomes the limitations of current methods. And more, the rules in this model can be easy realized in computer program.

Expression recognition using fuzzy spatio-temporal modeling

2008 ◽  
Vol 41 (1) ◽  
pp. 204-216 ◽  
Author(s):  
T. Xiang ◽  
M.K.H. Leung ◽  
S.Y. Cho
Keyword(s):  
Expression Recognition ◽  
Temporal Modeling ◽  
Spatio Temporal

Spatio-Temporal Modeling for Confirmed Cases of Lyme Disease in Virginia

2021 ◽  
pp. 101822
Author(s):  
Naresh Neupane ◽  
Ari Goldbloom-Helzner ◽  
Ali Arab
Keyword(s):  
Lyme Disease ◽  
Temporal Modeling ◽  
Spatio Temporal
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