Range-based Obstructed Nearest Neighbor Queries

Zhu, Huaijie; Yang, Xiaochun; Wang, Bin; Lee, Wang-Chien

doi:10.1145/2882903.2915234

Cited by 15 publications

(6 citation statements)

References 20 publications

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“…Those corners are important as they are usually the turning points for shortest paths in an obstructed space. In VG, two nodes are connected by a weighted edge if and only if there exists a straight line segment between them without crossing any obstacle [52,62]. In this paper, we exploit VG to define the DROP problem on dual worlds for the following reasons: 1) VG preserves the unobstructed shortest paths in the obstructed spatial space [52,60], simplifying the distance computation and reducing the computational complexity in processing obstructed spatial queries.…”

Section: Preliminariesmentioning

confidence: 99%

“…Sultana et al [52] study the obstructed group nearest neighbor (OGNN) query to find a rally point with the minimum aggregated distance. Range-based obstructed nearest neighbor search [62] extracts the nearest neighbors within a range for obstructed sequenced routes, where the route distance is minimized [4]. However, the above algorithms are designed for one world, instead of the entangled dual worlds, where the physical worlds of users are different from each other.…”

Section: Related Workmentioning

confidence: 99%

“…Visibility Graph. The notion of Visibility Graph (VG), widely used in computational geometries and obstructed spatial query processing [4,34,62], models obstacles as polygons and regards their corners as VG nodes. Those corners are important as they are usually the turning points for shortest paths in an obstructed space.…”

Section: Preliminariesmentioning

confidence: 99%

“…Some heuristics useful in geographic space, e.g., the triangular inequality, are not applicable here due to the obstacles appearing in both worlds. Moreover, traditional spatial index structures, e.g., R-Tree [15], M-Tree [8], and O-Tree [62] are designed for only one world instead of the entangled dual worlds, and thus do not handle the cost of RW operations. Finally, in a multi-user VR environment, the same path in the virtual world may be walked differently by users in their individual physical worlds.…”

Section: Introductionmentioning

confidence: 99%

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On VR Spatial Query for Dual Entangled Worlds

Lin

Lai

et al. 2019

Proceedings of the 28th ACM International Conference on Information and Knowledge Management

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With the rapid advent of Virtual Reality (VR) technology and virtual tour applications, there is a research need on spatial queries tailored for simultaneous movements in both the physical and virtual worlds. Traditional spatial queries, designed mainly for one world, do not consider the entangled dual worlds in VR. In this paper, we first investigate the fundamental shortest-path query in VR as the building block for spatial queries, aiming to avoid hitting boundaries and obstacles in the physical environment by leveraging Redirected Walking (RW) in Computer Graphics. Specifically, we first formulate Dual-world Redirected-walking Obstacle-free Path (DROP) to find the minimum-distance path in the virtual world, which is constrained by the RW cost in the physical world to ensure immersive experience in VR. We prove DROP is NP-hard and design a fully polynomial-time approximation scheme, Dual Entangled World Navigation (DEWN), by finding Minimum Immersion Loss Range (MIL Range). Afterward, we show that the existing spatial query algorithms and index structures can leverage DEWN as a building block to support kNN and range queries in the dual worlds of VR. Experimental results and a user study with implementation in HTC VIVE manifest that DEWN outperforms the baselines with smoother RW operations in various VR scenarios.

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Section: Preliminariesmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Preliminariesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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On VR Spatial Query for Dual Entangled Worlds

Lin

Lai

et al. 2019

Proceedings of the 28th ACM International Conference on Information and Knowledge Management

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“…The range nearest neighbor query (RNN query) retrieves the nearest neighbor for every point in a query range ( [8]- [10], etc.). We extend the point-DNN query to the range-DNN query, which searches for the DNNs w.r.t.…”

Section: Extension To Range-dnn Querymentioning

confidence: 99%

Direction-Aware Nearest Neighbor Query

Guo

Yang

2019

IEEE Access

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Although the direction aspect is as important as the distance aspect when retrieving spatial objects, the studies of direction-aware queries are limited. The direction-based surrounder query cannot guarantee good directional diversity. In this paper, we propose the direction-aware nearest neighbor query (DNN query), which can recommend the nearest objects and ensure that the results have good directional diversity. Given a query point q and an angular threshold θ, the DNN query searches for the nearest neighbors on various directions around q. The DNN query can apply to the scenario where the user searches for the nearest objects around him. It can also apply to the scenario where the user searches for the photos of a geographic object according to the locations where the photos are taken. It can find photos that capture different views of the query object. In this paper, we propose the point-DNN query, where the query object is a point, and extend it to the range-DNN query, where the query object is a rectangle. We design algorithms to answer the DNN queries and also conduct comprehensive experiments to evaluate the performances of the algorithms. INDEX TERMS Nearest neighbor query, direction-aware, spatial database.

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