Automatic tag generation and ranking for sensor-rich outdoor videos
MM '11 Proceedings of the 19th ACM international conference on Multimedia
See-to-retrieve: efficient processing of spatio-visual keyword queries
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Spatial search for K diverse-near neighbors
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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In this paper, we present a new type of spatial queries called Nearest Surrounder (NS) queries. An NS query determines the nearest polygon-shaped spatial objects (referred to as nearest surrounder objects) and their orientations with respect to a query point from an object set. Besides, we derive two NS query variants, namely, multitier NS (m-NS) queries and angle-constrained NS (ANS) queries. An m-NS query searches multiple layers of NS objects for the same range of angles from a query point. An ANS query searches for NS objects within a specified range of angles. To evaluate NS queries and their variants, we explore angle-based and distance-based bound properties of polygons, and devise two efficient algorithms, namely, Sweep and Ripple, based on R-tree. The algorithms access objects in an order according to their orientations and distances with respect to a given query point, respectively. They are efficient as they can finish a search with one index lookup. Besides, they can progressively deliver a query result. Through empirical studies, we evaluate the proposed algorithms and report their performance for both synthetic and real object sets.