• Title/Summary/Keyword: Spatio-temporal indexing

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Signature-based Indexing Scheme for Similar Sub-Trajectory Retrieval of Moving Objects (이동 객체의 유사 부분궤적 검색을 위한 시그니쳐-기반 색인 기법)

  • Shim, Choon-Bo;Chang, Jae-Woo
    • The KIPS Transactions:PartD
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    • v.11D no.2
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    • pp.247-258
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    • 2004
  • Recently, there have been researches on storage and retrieval technique of moving objects, which are highly concerned by user in database application area such as video databases, spatio-temporal databases, and mobile databases. In this paper, we propose a new signature-based indexing scheme which supports similar sub-trajectory retrieval at well as good retrieval performance on moving objects trajectories. Our signature-based indexing scheme is classified into concatenated signature-based indexing scheme for similar sub-trajectory retrieval, entitled CISR scheme and superimposed signature-based indexing scheme for similar sub-trajectory retrieval, entitled SISR scheme according to generation method of trajectory signature based on trajectory data of moving object. Our indexing scheme can improve retrieval performance by reducing a large number of disk access on data file because it first scans all signatures and does filtering before accessing the data file. In addition, we can encourage retrieval efficiency by appling k-warping algorithm to measure the similarity between query trajectory and data trajectory. Final]y, we evaluate the performance on sequential scan method(SeqScan), CISR scheme, and SISR scheme in terms of data insertion time, retrieval time, and storage overhead. We show from our experimental results that both CISR scheme and SISR scheme are better than sequential scan in terms of retrieval performance and SISR scheme is especially superior to the CISR scheme.

Distributed Moving Objects Management System for a Smart Black Box

  • Lee, Hyunbyung;Song, Seokil
    • International Journal of Contents
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    • v.14 no.1
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    • pp.28-33
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    • 2018
  • In this paper, we design and implement a distributed, moving objects management system for processing locations and sensor data from smart black boxes. The proposed system is designed and implemented based on Apache Kafka, Apache Spark & Spark Streaming, Hbase, HDFS. Apache Kafka is used to collect the data from smart black boxes and queries from users. Received location data from smart black boxes and queries from users becomes input of Apache Spark Streaming. Apache Spark Streaming preprocesses the input data for indexing. Recent location data and indexes are stored in-memory managed by Apache Spark. Old data and indexes are flushed into HBase later. We perform experiments to show the throughput of the index manager. Finally, we describe the implementation detail in Scala function level.

A Study on Spatial-temporal indexing for querying current and past positions (현재와 과거 위치 질의를 위한 시공간 색인에 관한 연구)

  • Jun, Bong-Gi
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.8 no.6
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    • pp.1250-1256
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    • 2004
  • The movement of continuously changing positions should be stored and indexed for querying current and past positions. A simple extension of the original R-tree to add time as another dimension, called 3D R-tree, does not handle current position queries and does not address the problem of low space utilization due to high overlap of index nodes. In this paper, 1 propose the dynamic splitting policy for improving the 3D R-tree in order to improve space utilization of split nodes. 1 also extend the original 3D R-tree by introducing a new tagged index structure for being able to query the current and past positions of moving objects. 1 found out that my extension of the original R-tree, called the tagged dynamic 3DR-tree, outperforms both the 3D R-tree and 75-tree when querying current and past position.

Range Query Processing using Space and Time Filtering in Fixed Grid Indexing (고정 그리드 인덱싱에서 공간과 시간 필터링을 이용한 범위 질의 처리)

  • Jeon, Se-Gil;Nah, Yun-Mook
    • The KIPS Transactions:PartD
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    • v.11D no.4
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    • pp.835-844
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    • 2004
  • Recently, the location-based service for moving customers is becoming one of the most important service in mobile communication area. For moving object applications, there are lots of update operations and such update loads are concentrated on some particular area unevenly. Range queries, whose range can be window or circular, are the most essential query types in LBS. We need to distinguish completely contained cells from partially contained cells in those range queries. Also, it is necessary to consider temporal dimension to filter out qualifying objects correctly. In this paper, we adopt two-level index structures with fixed grid file structures in the second level, which are designed to minimize update operations. We propose a spatial ceil filtering method using VP filtering and a combined spatio-temporal filtering method using time gone concepts. Some experimental results are shown for various window queries and circular queries with different filtering combinations to show the performance tradeoffs of the proposed methods.

Fast Scene Change Detection Using Macro Block Information and Spatio-temporal Histogram (매크로 블록 정보와 시공간 히스토그램을 이용한 빠른 장면전환검출)

  • Jin, Ju-Kyong;Cho, Ju-Hee;Jeong, Jae-Hyup;Jeong, Dong-Suk
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.1
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    • pp.141-148
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    • 2011
  • Most of the previous works on scene change detection algorithm focus on the detection of abrupt rather than gradual changes. In general, gradual scene change detection algorithms require heavy computation. Some of those approaches don't consider the error factors such as flashlights, camera or object movements, and special effects. Many scenes change detection algorithms based on the histogram show better performances than other approaches, but they have computation load problem. In this paper, we proposed a scene change detection algorithm with fast and accurate performance using the vertical and horizontal blocked slice images and their macro block informations. We apply graph cut partitioning algorithm for clustering and partitioning of video sequence using generated spatio-temporal histogram. When making spatio-temporal histogram, we only use the central block on vertical and horizontal direction for performance improvement. To detect camera and object movement as well as various special effects accurately, we utilize the motion vector and type information of the macro block.

A Node Relocation Strategy of Trajectory Indexes for Efficient Processing of Spatiotemporal Range Queries (효율적인 시공간 영역 질의 처리를 위한 궤적 색인의 노드 재배치 전략)

  • Lim Duksung;Cho Daesoo;Hong Bonghee
    • Journal of KIISE:Databases
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    • v.31 no.6
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    • pp.664-674
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    • 2004
  • The trajectory preservation property that stores only one trajectory in a leaf node is the most important feature of an index structure, such as the TB-tree for retrieving object's moving paths in the spatio-temporal space. It performs well in trajectory-related queries such as navigational queries and combined queries. But, the MBR of non-leaf nodes in the TB-tree have large amounts of dead space because trajectory preservation is achieved at the sacrifice of the spatial locality of trajectories. As dead space increases, the overlap between nodes also increases, and, thus, the classical range query cost increases. We present a new split policy and entry relocation policies, which have no deterioration of the performance for trajectory-related queries, for improving the performance of range queries. To maximally reduce the dead space of a non-leaf node's MBR, the Maximal Area Reduction (MAR) policy is used as a split policy for non-leaf nodes. The entry relocation policy induces entries in non-leaf nodes to exchange each other for the purpose of reducing dead spaces in these nodes. We propose two algorithms for the entry relocation policy, and evaluate the performance studies of new algorithms comparing to the TB-tree under a varying set of spatio-temporal queries.

Update Frequency Reducing Method of Spatio-Temporal Big Data based on MapReduce (MapReduce와 시공간 데이터를 이용한 빅 데이터 크기의 이동객체 갱신 횟수 감소 기법)

  • Choi, Youn-Gwon;Baek, Sung-Ha;Kim, Gyung-Bae;Bae, Hae-Young
    • Spatial Information Research
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    • v.20 no.2
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    • pp.137-153
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    • 2012
  • Until now, many indexing methods that can reduce update cost have been proposed for managing massive moving objects. Because indexing methods for moving objects have to be updated periodically for managing moving objects that change their location data frequently. However these kinds indexing methods occur big load that exceed system capacity when the number of moving objects increase dramatically. In this paper, we propose the update frequency reducing method to combine MapReduce and existing indices. We use the update request grouping method for each moving object by using MapReduce. We decide to update by comparing the latest data and the oldest data in grouping data. We reduce update frequency by updating the latest data only. When update is delayed, for the data should not be lost and updated periodically, we store the data in a certain period of time in the hash table that keep previous update data. By the performance evaluation, we can prove that the proposed method reduces the update frequency by comparison with methods that are not applied the proposed method.

Trajectory Indexing for Efficient Processing of Range Queries (영역 질의의 효과적인 처리를 위한 궤적 인덱싱)

  • Cha, Chang-Il;Kim, Sang-Wook;Won, Jung-Im
    • The KIPS Transactions:PartD
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    • v.16D no.4
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    • pp.487-496
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    • 2009
  • This paper addresses an indexing scheme capable of efficiently processing range queries in a large-scale trajectory database. After discussing the drawbacks of previous indexing schemes, we propose a new scheme that divides the temporal dimension into multiple time intervals and then, by this interval, builds an index for the line segments. Additionally, a supplementary index is built for the line segments within each time interval. This scheme can make a dramatic improvement in the performance of insert and search operations using a main memory index, particularly for the time interval consisting of the segments taken by those objects which are currently moving or have just completed their movements, as contrast to the previous schemes that store the index totally on the disk. Each time interval index is built as follows: First, the extent of the spatial dimension is divided onto multiple spatial cells to which the line segments are assigned evenly. We use a 2D-tree to maintain information on those cells. Then, for each cell, an additional 3D $R^*$-tree is created on the spatio-temporal space (x, y, t). Such a multi-level indexing strategy can cure the shortcomings of the legacy schemes. Performance results obtained from intensive experiments show that our scheme enhances the performance of retrieve operations by 3$\sim$10 times, with much less storage space.

Video retrieval method using non-parametric based motion classification (비-파라미터 기반의 움직임 분류를 통한 비디오 검색 기법)

  • Kim Nac-Woo;Choi Jong-Soo
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.43 no.2 s.308
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    • pp.1-11
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    • 2006
  • In this paper, we propose the novel video retrieval algorithm using non-parametric based motion classification in the shot-based video indexing structure. The proposed system firstly gets the key frame and motion information from each shot segmented by scene change detection method, and then extracts visual features and non-parametric based motion information from them. Finally, we construct real-time retrieval system supporting similarity comparison of these spatio-temporal features. After the normalized motion vector fields is created from MPEG compressed stream, the extraction of non-parametric based motion feature is effectively achieved by discretizing each normalized motion vectors into various angle bins, and considering a mean, a variance, and a direction of these bins. We use the edge-based spatial descriptor to extract the visual feature in key frames. Experimental evidence shows that our algorithm outperforms other video retrieval methods for image indexing and retrieval. To index the feature vectors, we use R*-tree structures.

An Improved Split Algorithm for Indexing of Moving Object Trajectories (이동 객체 궤적의 색인을 위한 개선된 분할 알고리즘)

  • Jeon, Hyun-Jun;Park, Ju-Hyun;Park, Hee-Suk;Cho, Woo-Hyun
    • The KIPS Transactions:PartD
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    • v.16D no.2
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    • pp.161-168
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    • 2009
  • Recently, use of various position base servicesthat collect position information for moving object and utilize in real life is increasing by the development of wireless network technology. Accordingly, new index structures are required to efficiently retrieve the consecutive positions of moving objects. This paper addresses an improved trajectory split algorithm for the purpose of efficiently supporting spatio-temporal range queries using index structures that use Minimum Bounding Rectangles(MBR) as trajectory approximations. We consider volume of Extended Minimum Bounding Rectangles (EMBR) to be determined by average size of range queries. Also, Use a priority queue to speed up our process. This algorithm gives in general sub-optimal solutions with respect to search space. Our improved trajectory split algorithm is going to derive minimizing volume of EMBRs better than previously proposed split algorithm.