CASIA OpenIR  > 模式识别国家重点实验室  > 图像与视频分析
Effective logo retrieval with adaptive local feature selection
Fu, Jianlong; Wang, Jinqiao; Lu, Hanqing
2010
Conference NameMM'10 - the ACM Multimedia 2010 International Conference
Source PublicationACM Multimedia Conferenc (MM)
Pages971-974
Conference Date2010
Conference PlaceFirenze
AbstractTowards building a practical large-scale logo retrieval system, we
propose a novel approach to extract and combine local features
for effective logo retrieval. Instead of global feature extraction by
modeling the web logo as a whole, we extract the local feature
phrases to form a visual codebook and build an inverted file
storing the features to accelerate the indexing process. Then we
divide logos into several groups according to local feature type
based on which feature can model the logo best and naming as
“Point-type”, “Shape-type” and “Patch-type”. We develop a
strategy of adaptive feature selection by a weight updating
mechanism. To evaluate the performance, we have built a new
challenging dataset which consists of 60 international
corporations’ logos. Experiments and comparisons demonstrate
the superior performance to previous retrieval algorithms.
KeywordEffective Logo Retrieval Adaptive Local Feature Selection
Indexed ByEI
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/4580
Collection模式识别国家重点实验室_图像与视频分析
Corresponding AuthorWang, Jinqiao
Recommended Citation
GB/T 7714
Fu, Jianlong,Wang, Jinqiao,Lu, Hanqing. Effective logo retrieval with adaptive local feature selection[C],2010:971-974.
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