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Efficient BOF Generation and Compression for On-Device Mobile Visual Location Recognition
Apr.-June 2014 (vol. 21 no. 2)
pp. 32-41
Tao Guan, HuaZhong University of Science and Technology
Yunfeng He, HuaZhong University of Science and Technology
Liya Duan, HuaZhong University of Science and Technology
Jianzhong Yang, HuaZhong University of Science and Technology
Juan Gao, HuaZhong University of Science and Technology
Junqing Yu, HuaZhong University of Science and Technology
Existing mobile visual location recognition (MVLR) applications typically rely on bag-of-features (BOF) representation, which shows superior performance in retrieval accuracy. However, although the BOF framework is promising, it is not compact enough for on-device MVLR. The authors have made two contributions to the design of a BOF-based on-device MVLR system. First, to generate BOF descriptors, they propose a memory-efficient approximate nearest-neighbor search algorithm by combining residual vector quantization (RVQ) and tree-structured RVQ (TSRVQ). Second, they implemented a GPS-based and heading-aware RankBoost algorithm to reduce the dimensionality of the BOF descriptors. The authors evaluate the effectiveness of the proposed algorithms on an HTC mobile phone. Their work applies to on-device MVLR in city-scale workspaces.
Index Terms:
Data visualization,Mobile communication,Vocabulary,Quantization (signal),Image recognition,Algorithm design and analysis,RankBoost,multimedia,mobile visual location recognition,on-device,bag-of-features
Citation:
Tao Guan, Yunfeng He, Liya Duan, Jianzhong Yang, Juan Gao, Junqing Yu, "Efficient BOF Generation and Compression for On-Device Mobile Visual Location Recognition," IEEE Multimedia, vol. 21, no. 2, pp. 32-41, Apr.-June 2014, doi:10.1109/MMUL.2013.31
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