Enhanced simultaneous localization and map building

Lin, Tung-Yuan; Hsu, Chen-Chien; Wang, Wei Yen; Wang, Yin-Tien

doi:10.1109/cacs.2014.7097174

Cited by 1 publication

(1 citation statement)

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“…Similar to LSH, the establishment of the hash function is also a major concern in KLSH. Thus, in order to calculate the collision probability between the input query items and database items, we must calculate the similarity between any two items in the database [20,21]. According to previous studies [22,23], the definition of the LSH function can be extended from (6) into the following form:…”

Section: Image Classification Model Based On Homogeneous Kernel Scalamentioning

confidence: 99%

Approximately Nearest Neighborhood Image Search Using Unsupervised Hashing via Homogeneous Kernels

2018

Complexity

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We propose an approximation search algorithm that uses additive homogeneous kernel mapping to search for an image approximation based on kernelized locality-sensitive hashing. To address problems related to the unstable search accuracy of an unsupervised image hashing function and degradation of the search-time performance with increases in the number of hashing bits, we propose a method that combines additive explicit homogeneous kernel mapping and image feature histograms to construct a search algorithm based on a locality-sensitive hashing function. Moreover, to address the problem of semantic gaps caused by using image data that lack type information in semantic modeling, we describe an approximation searching algorithm based on the homogeneous kernel mapping of similarities between pairs of images and dissimilar constraint relationships. Our image search experiments confirmed that the proposed algorithm can construct a locality-sensitive hash function more accurately, thereby effectively improving the similarity search performance.

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Section: Image Classification Model Based On Homogeneous Kernel Scalamentioning

confidence: 99%

Approximately Nearest Neighborhood Image Search Using Unsupervised Hashing via Homogeneous Kernels

2018

Complexity

View full text Add to dashboard Cite

show abstract

Enhanced simultaneous localization and map building

Cited by 1 publication

References 8 publications

Approximately Nearest Neighborhood Image Search Using Unsupervised Hashing via Homogeneous Kernels

Approximately Nearest Neighborhood Image Search Using Unsupervised Hashing via Homogeneous Kernels

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