• Journal of Korea Game Society
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• v.13 no.4
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• pp.25-34
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• 2013

Spatial partitioning trees are needed for processing collision detections efficiently. In order to select split planes for spatial partitioning trees, the tree balance and the number of polygons overlapped with the split plane should be considered. In this paper, the heuristic algorithm controlling weight values of tree build criteria is proposed for spatial partitioning trees of 3D games. As the weight values are changed, tree build time, T-junction elimination time which can cause visual artifacts in splitting polygons overlapped with the split plane, rendering speed (frame per second: FPS) according to tree balance are analysed under 3D game simulations.

• Spatial Information Research
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• v.19 no.2
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• pp.47-56
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• 2011

Typical tree-based spatial index structures are divided into a data-partitioning index structure such as R-Tree and a space-partitioning index structure such as KD-Tree. In recent years, researches on hybrid index structures combining advantages of these index structures have been performed extensively. However, because the split boundary extension of the node to which a new spatial object is inserted may extend split boundaries of other neighbor nodes in existing researches, overlaps between nodes are increased and the query processing cost is raised. In this paper, we propose a hybrid index structure, called SQR-Tree that can support efficient processing of spatial queries to solve these problems. SQR-Tree is a combination of SQ-Tree(Spatial Quad- Tree) which is an extended Quad-Tree to process non-size spatial objects and R-Tree which actually stores spatial objects associated with each leaf node of SQ-Tree. Because each SQR-Tree node has an MBR containing sub-nodes, the split boundary of a node will be extended independently and overlaps between nodes can be reduced. In addition, a spatial object is inserted into R-Tree in each split data space and SQ-Tree is used to identify each split data space. Since only R-Trees of SQR-Tree in the query area are accessed to process a spatial query, query processing cost can be reduced. Finally, we proved superiority of SQR-Tree through experiments.

• KIEAE Journal
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• v.11 no.6
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• pp.95-100
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• 2011

Although Space Syntax is a well-known technique for spatial analysis, debates have taken place among some researchers because the Space Syntax discards geometric information as both shapes and sizes of spaces, and hence may cause some inconsistencies. Therefore, this study aims at developing methods to recognize and manage spatial shapes for more precise space syntax analysis. To reach this goal, this study employed both a graph theory and binary spatial partitioning (BSP) tree to recognize and manage spatial information. As a result, spatial shapes and sizes could be recognized by checking loops in graph converted from spatial shapes of built environment. Each spatial shape could be managed sequentially by BSP tree with hierarchical structure. Through such recognition and management processes, convex maps composed of the fattest and fewest convex spaces could be drawn. In conclusion, we hope that the methods developed here will be useful for urban planning to find appropriate purposes of spaces to satisfy the sustainability of built environment on the basis of the spatial and social relationships in urban spaces.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.5244-5259
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• 2019

With the continuous development of LBS (Location Based Service) applications, privacy protection has become an urgent problem to be solved. Differential privacy technology is based on strict mathematical theory that provides strong privacy guarantees where it supposes that the attacker has the worst-case background knowledge and that knowledge has been applied to different research directions such as data query, release, and mining. The difficulty of this research is how to ensure data availability while protecting privacy. Spatial multidimensional data are usually released by partitioning the domain into disjointed subsets, then generating a hierarchical index. The traditional data-dependent partition methods need to allocate a part of the privacy budgets for the partitioning process and split the budget among all the steps, which is inefficient. To address such issues, a novel two-step partition algorithm is proposed. First, we partition the original dataset into fixed grids, inject noise and synthesize a dataset according to the noisy count. Second, we perform IH-Tree (Improved H-Tree) partition on the synthetic dataset and use the resulting partition keys to split the original dataset. The algorithm can save the privacy budget allocated to the partitioning process and obtain a more accurate release. The algorithm has been tested on three real-world datasets and compares the accuracy with the state-of-the-art algorithms. The experimental results show that the relative errors of the range query are considerably reduced, especially on the large scale dataset.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.961-968
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• 2018

Recently, researches on automatic recognition of human activities have been actively carried out with the emergence of various intelligent systems. Since a large amount of visual data can be secured through Closed Circuit Television, it is required to recognize human behavior in a dynamic situation rather than a static situation. In this paper, we propose new intelligent human activity recognition model using the trajectory information extracted from the video sequence. The proposed model consists of three steps: segmentation and partitioning of trajectory step, feature extraction step, and behavioral learning step. First, the entire trajectory is fuzzy partitioned according to the motion characteristics, and then temporal features and spatial features are extracted. Using the extracted features, four pedestrian behaviors were modeled by decision tree learning algorithm and performance evaluation was performed. The experiments in this paper were conducted using Caviar data sets. Experimental results show that trajectory provides good activity recognition accuracy by extracting instantaneous property and distinctive regional property.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.4
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• pp.7-14
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• 2003

A number of embedded wavelet image coding methods have been proposed since the introduction of EZW(Embedded Zerotree Wavelet) algorithm. A common characteristic of these methods is that they use fundamental ideas found in the EZW algorithm. Especially, one of these methods is the SPIHT(Set Partitioning in Hierarchy Trees) algorithm, which became very popular since it was able to achieve equal or better performance than EZW without having to use an arithmetic encoder. In this paper We propose a recursive set partitioning in hierarchy trees(RSPIHT) algorithm for embedded image coding and evaluate it's effectiveness experimentally. The proposed RSPIHT algorithm takes the simple and regular form and the worst case time complexity of O(n). From the viewpoint of processing time, the RSPIHT algorithm takes about 16.4% improvement in average than the SPIHT algorithm at T-layer over 4 of experimental images. Also from the viewpoint of coding rate, the RSPIHT algorithm takes similar results at T-layer under 7 but the improved results at other T-layer of experimental images.

• The KIPS Transactions:PartB
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• v.10B no.5
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• pp.575-578
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• 2003

SPIHT algorithm is a wavelet based fast and effective technique for image compression. It uses a list structure to store status information which is generated during set-partitioning of zero-tree. Usually, this requires lots of additional memory depending on how high the bit-rate is. Therefore, in this paper, we propose a new technique called MZP-DFS, which needs no additional memory when running SPIHT algorithm. It traverses a spatial-tree according to DFS and eliminates additional memory as it uses test-functions for encoding and LSB bits of coefficients for decoding respectively. This method yields nearly the same performance as SPIHT. This may be desirable in hardware implementation because no additional memory is required. Moreover. it exploits parallelism to process each spatial-tree that it can be applied well in real-time image compression.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.814-821
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• 2002

The SPIHT(set partitioning in hierarchical tree) is efficient and well-known in the zerotree coding algorithm. However SPIHT's high memory requirement is a major difficulty for hardware implementation. In this paper we propose low-memory and fast zerotree algorithm. We present following three methods for reduced memory and fst coding speed. First, wavelet transform by lifting has a low memory requirement and reduced complexity than traditional filter bank implementation. The second method is to divide the wavelet coefficients into a block. Finally, we use NLS algorithm proposed by Wheeler and Pearlman in our codec. Performance of NLS is nearly same as SPIHT and reveals low and fixed memory and fast coding speed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.4 no.3
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• pp.263-269
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• 2003

This paper focuses on lossy medical image compression methods for medical images that operate on three-dimensional(3D) irreversible integer wavelet transform. We offer an application of the Set Partitioning in Hierarchical Trees(SPIHT) algorithm〔l-3〕to medical images, using a 3-D wavelet decomposition and a 3-D spatial dependence tree. The wavelet decomposition is accomplished with integer wavelet filters implemented with the lifting method, where careful scaling and truncations keep the integer precision small and the transform unitary. As the compression rate increases, the boundaries between adjacent coding units become increasingly visible. Unlike video, the volume image is examined under static condition, and must not exhibit such boundary artifacts. In order to eliminate them, we utilize overlapping at axial boundaries between adjacent coding units. We have tested our encoder on medical images using different integer filters. Results show that our algorithm with certain filters performs as well. The improvement is visibly manifested as fewer ringing artifacts and noticeably better reconstruction of low contrast.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.5_6
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• pp.321-327
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• 2004

SPIHT algorithm is a wavelet based fast and effective technique for image compression. It uses a list structure to store status information which is generated during set-partitioning of toro-tree. Usually, this requires lots of additional memory depending on how high the bit-rate is. Therefore, in this paper, we propose a new technique called MZC-BFS, which needs no additional memory when running SPIHT algorithm. It explicitly performs a breadth first search of the spatial-tree using peano-code and eliminates additional memory as it uses pre-status significant test for encoding and LSB bits of some coefficients for decoding respectively. This method yields nearly the same performance as SPIHT. This may be desirable in fast and simple hardware implementation and reduces the cost of production because no lists and additional memory are required.