Indexing Mobile Objects

2011 ◽  
pp. 315-338
Author(s):  
Panayiotis Bozanis
Keyword(s):  
Moving Objects ◽  
Object Location ◽  
Location Information ◽  
Substantial Part ◽  
Mobile Object ◽  
Application Area ◽  
Mobile Objects ◽  
Object Indexing ◽  
Crucial Part ◽  
Fast Access

Mobile computing emerged as a new application area due to recent advances in communication and positioning technology. As David Lomet (2002) notices, a substantial part of the conducted work refers to keeping track of the position of moving objects (automobiles, people, etc.) at any point in time. This information is very critical for decision making, and, since objects’ locations may change with relatively high frequency, this calls for providing fast access to object location information, thus rendering the indexing of moving objects a very interesting as well as crucial part of the area. In this chapter we present an overview on advances made in databases during the last few years in the area of mobile object indexing, and discuss issues that remain open or, probably, are interesting for related applications.

Indexing Mobile Objects

2009 ◽  
pp. 313-333
Author(s):  
Panayiotis Bozanis
Keyword(s):  
Moving Objects ◽  
Object Location ◽  
Location Information ◽  
Substantial Part ◽  
Mobile Object ◽  
Application Area ◽  
Mobile Objects ◽  
Object Indexing ◽  
Crucial Part ◽  
Fast Access

Mobile computing emerged as a new application area due to recent advances in communication and positioning technology. As David Lomet (2002) notices, a substantial part of the conducted work refers to keeping track of the position of moving objects (automobiles, people, etc.) at any point in time. This information is very critical for decision making, and, since objects’ locations may change with relatively high frequency, this calls for providing fast access to object location information, thus rendering the indexing of moving objects a very interesting as well as crucial part of the area. In this chapter we present an overview on advances made in databases during the last few years in the area of mobile object indexing, and discuss issues that remain open or, probably, are interesting for related applications.

scholarly journals Path Planning for Mobile Objects in Four-Dimension Based on Particle Swarm Optimization Method with Penalty Function

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Yong Ma ◽  
M. Zamirian ◽  
Yadong Yang ◽  
Yanmin Xu ◽  
Jing Zhang
Keyword(s):  
Particle Swarm Optimization ◽  
Penalty Function ◽  
Particle Swarm ◽  
Goal Function ◽  
Optimization Method ◽  
Mobile Object ◽  
Time Varying ◽  
Swarm Optimization ◽  
Calculus Of Variation ◽  
Mobile Objects

We present one algorithm based on particle swarm optimization (PSO) with penalty function to determine the conflict-free path for mobile objects in four-dimension (three spatial and one-time dimensions) with obstacles. The shortest path of the mobile object is set as goal function, which is constrained by conflict-free criterion, path smoothness, and velocity and acceleration requirements. This problem is formulated as a calculus of variation problem (CVP). With parametrization method, the CVP is converted to a time-varying nonlinear programming problem (TNLPP). Constraints of TNLPP are transformed to general TNLPP without any constraints through penalty functions. Then, by using a little calculations and applying the algorithm PSO, the solution of the CVP is consequently obtained. Approach efficiency is confirmed by numerical examples.

scholarly journals EXTRACTING MOBILE OBJECTS IN IMAGES USING A VELODYNE LIDAR POINT CLOUD

2015 ◽  
Vol II-3/W4 ◽  
pp. 247-253 ◽  
Author(s):  
B. Vallet ◽  
W. Xiao ◽  
M. Brédif
Keyword(s):  
Point Cloud ◽  
Mobile Object ◽  
Object A ◽  
Mobile Objects ◽  
Dempster Shafer Theory ◽  
Static Part ◽  
Shafer Theory

This paper presents a full pipeline to extract mobile objects in images based on a simultaneous laser acquisition with a Velodyne scanner. The point cloud is first analysed to extract mobile objects in 3D. This is done using Dempster-Shafer theory and it results in weights telling for each points if it corresponds to a mobile object, a fixed object or if no decision can be made based on the data (unknown). These weights are projected in an image acquired simultaneously and used to segment the image between the mobile and the static part of the scene.

scholarly journals Conceptual distinctiveness does not improve visual working memory for objects but aids object-location binding

2021 ◽  
Author(s):  
Yuri Markov ◽  
Igor Utochkin
Keyword(s):  
Working Memory ◽  
Visual Working Memory ◽  
Competitive Interactions ◽  
Object Location ◽  
Location Information ◽  
Limited Capacity ◽  
Common Features ◽  
Categorical Information ◽  
Location Binding ◽  
Different Sources

Visual working memory (VWM) is prone to interference from stored items competing for its limited capacity. These competitive interactions can arise from different sources. For example, one such source is poor item distinctiveness causing a failure to discriminate between items sharing common features. Another source of interference is imperfect binding, a problem of determining which of the remembered features belonged to which object or which item was in which location. In two experiments, we studied how the conceptual distinctiveness of real-world objects (i.e., whether the objects belong to the same or different basic categories) affects VWM for objects and object-location binding. In Experiment 1, we found that distinctiveness did not affect memory for object identities or for locations, but low-distinctive objects were more frequently reported at “swapped” locations that originally went with different objects. In Experiment 2 we found evidence that the effect of distinctiveness on the object-location swaps was due to the use of categorical information for binding. In particular, we found that observers swapped the location of a tested object with another object from the same category more frequently than with any of the objects from another category. This suggests that observers can use some coarse category-location information when objects are conceptually distinct. Taken together, our findings suggest that object distinction and object-location binding act upon different components of VWM.

Mobile Object Indexing

2016 ◽  
pp. 1-11
Author(s):  
George Kollios ◽  
Vassilis J. Tsotras ◽  
Dimitrios Gunopulos
Keyword(s):  
Mobile Object ◽  
Object Indexing

scholarly journals Mobile Location Indexing Based On Synthetic Moving Objects

2019 ◽  
Vol 9 (4) ◽  
pp. 2556
Author(s):  
Thu Thu Zan ◽  
Sabai Phyu
Keyword(s):  
Performance Evaluation ◽  
Location Privacy ◽  
Moving Objects ◽  
Nearest Neighbor ◽  
Data Access ◽  
Nearest Neighbor Search ◽  
Index Structure ◽  
Mobile Objects ◽  
Neighbor Search ◽  
Privacy And Confidentiality

Today, the number of researches based on the data they move known as mobile objects indexing came out from the traditional static one. There are some indexing approaches to handle the complicated moving positions. One of the suitable ideas is pre-ordering these objects before building index structure. In this paper, a structure, a presorted-nearest index tree algorithm is proposed that allowed maintaining, updating, and range querying mobile objects within the desired period. Besides, it gives the advantage of an index structure to easy data access and fast query along with the retrieving nearest locations from a location point in the index structure. A synthetic mobile position dataset is also proposed for performance evaluation so that it is free from location privacy and confidentiality. The detail experimental results are discussed together with the performance evaluation of KDtree-based index structure. Both approaches are similarly efficient in range searching. However, the proposed approach is especially much more save time for the nearest neighbor search within a range than KD tree-based calculation.

scholarly journals The Implementation of a Red Object Tracking Algorithm with a Single, Static Camera

2021 ◽  
Vol 12 (1) ◽  
pp. 40
Author(s):  
Ali Arshad ◽  
Saman Cheema ◽  
Umair Ahsan
Keyword(s):  
Image Processing ◽  
Object Tracking ◽  
Activity Recognition ◽  
Moving Objects ◽  
Processing Algorithm ◽  
Location Information ◽  
Surveillance Systems ◽  
Image Processing Algorithm ◽  
Adaptive Image Processing ◽  
Increasing Demand

In recent years, activity recognition and object tracking are receiving extensive attention due to the increasing demand for adaptable surveillance systems. Activity recognition is guided by the parameters such as the shape, size, and color of the object. This article purposes an examination of the performance of existing color-based object detection and tracking algorithms using thermal/visual camera-based video steaming in MATLAB. A framework is developed to detect and track red moving objects in real time. Detection is carried out based on the location information acquired from an adaptive image processing algorithm. Coordinate extraction is followed by tracking and locking the object with the help of a laser barrel. The movement of the laser barrel is controlled with the help of an 8051 microcontroller. Location information is communicated from the image-processing algorithm to the microcontroller serially. During implementation, a single static camera is used that provides 30 frames per second. For each frame, 88 ms are required to complete all three steps from detection to tracking, to locking, so a processing speed of 12 frames per second is implemented. This repetition makes the setup adaptive to the environment despite the presence of a single static camera. This setup can handle multiple objects with shades of red and has demonstrated equally good results in varying outdoor conditions. Currently, the setup can lock only single targets, but the capacity of the system can be increased with the installation of multiple cameras and laser barrels.

scholarly journals A METHOD FOR CHOOSING A STRATEGY FOR THE BEHAVIOR OF A CELLULAR AUTOMATON WHEN SOLVING THE PROBLEM OF FINDING TARGETS BY A GROUP OF MOVING OBJECTS

2021 ◽  
Vol 5 (4) ◽  
pp. 42-48
Author(s):  
Valerii Chystov ◽  
Iryna Zakharchenko ◽  
Vladislava Pavlenko ◽  
Maksim Pavlenko
Keyword(s):  
Cellular Automaton ◽  
Moving Objects ◽  
Group Behavior ◽  
Behavioral Models ◽  
Behavioral Systems ◽  
Mobile Objects ◽  
Key Characteristics ◽  
Complete Search ◽  
Adaptive Choice ◽  
Two Parameters

Currently, a large number of different mathematical models and methods aimed at solving problems of multidimensional optimization and modeling of complex behavioral systems have been developed. One of the areas of search for solutions is the search for solutions in conditions of incomplete information and the need to take into account changing external factors. Often such problems are solved by the method of complete search. In some conditions, the method of complete search can be significantly improved through the implementation and use of behavioral models of natural formations. Examples of such formations can be group behavior of insects, birds, fish, various flocks, etc. The idea of copying group activity of a shoal of fishes at the decision of problems of joint activity on extraction of food is used in work. The reasoning based on the simulation of the behavior of such a natural object allowed to justify the choice as a mathematical model - cellular automata. The paper examines the key features of such a model. Modeling of his work is carried out, strategies of behavior of group of mobile objects at search of the purposes are developed, key characteristics are investigated and the method of adaptive choice of strategy and change of rules of behavior taking into account features of the solved problem is developed. The search strategy is implemented in the work, which takes into account the need to solve the optimization problem on two parameters. The obtained results testify to the high descriptive possibility of such an approach, the possibility of finding the optimal strategy for the behavior of the cellular automaton and the formalization of the process of selecting the parameters of its operation. A further improvement of this approach can be the implementation of simulation to study the properties of the developed model, the formation of the optimal set of rules and parameters of the machine for the whole set of tasks.

Benchmarking and Data Generation in Moving Objects Databases

2005 ◽  
pp. 23-28 ◽  
Author(s):  
Theodoros Tzouramanis
Keyword(s):  
Mobile Communication ◽  
Moving Objects ◽  
Query Languages ◽  
Location Information ◽  
Navigation Systems ◽  
Data Generation ◽  
Access Methods ◽  
Future Projections ◽  
Storage And Retrieval ◽  
Moving Objects Databases

Moving objects databases (MODs) provide the framework for the efficient storage and retrieval of the changing position of continuously moving objects. This includes the current and past locations of moving objects and the support of spatial queries that refer to historical location information and future projections as well. Nowadays, new spatiotemporal applications that require tracking and recording the trajectories of moving objects online are emerging. Digital battlefields, traffic supervision, mobile communication, navigation systems, and geographic information systems (GIS) are among these applications. Towards this goal, during recent years many efforts have focused on MOD formalism, data models, query languages, visualization, and access methods (Guting et al., 2000; Saltenis & Jensen, 2002; Sistla, Wolfson, Chamberlain, & Dao, 1997). However, little work has appeared on benchmarking.

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