Relevance Feedback Based Retrieval of Cloth Image with Focus on Collar Design

Shimizu, Kazumi; Yang, Wei; Toyoura, Masahiro; Mao, Xiaoyang

doi:10.1109/cw.2015.70

Cited by 2 publications

(3 citation statements)

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“…To validate the above proposed ideas and methods, a series of experiments are conducted. The experiment results presented in [12] could not provide sufficient validation to the proposed methods. First, only four subjects were involved in the experiments and thus the results might not be reliable enough.…”

Section: Introductionmentioning

confidence: 55%

“…The other is its number used in the experiment as it should be easier to find a certain collar type if there are more images of such type in the database. The experiments presented in [12], however, ignored these factors completely. To solve the problems, in our new experiments, each subject is asked to test all the ten collar types plus one front designs for the three different combinations of feature vectors: Spread + SBF, Spread + SABF and Spread + SSBF.…”

Section: Methodsmentioning

confidence: 91%

“…To eliminate the bias caused by the population of collar types in the database, the number of images of each collar type is used to weight the score inversely when compare the average score of the three feature vectors for all images. While previous experiments used only four subjects [12], we improved the reliability of experiment results by expanding the number of subjects to 10. The ten subjects are female college students from school of nursing.…”

Section: Methodsmentioning

confidence: 93%

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Retrieval of clothing images based on relevance feedback with focus on collar designs

Toyoura

Shimizu

et al. 2016

Vis Comput

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The content-based image retrieval methods are developed to help people find what they desire based on preferred images instead of linguistic information. This paper focuses on capturing the image features representing details of the collar designs, which is important for people to choose clothing. The quality of the feature extraction methods is important for the queries. This paper presents several new methods for the collar-design feature extraction. A prototype of clothing image retrieval system based on relevance feedback approach and optimum-path forest algorithm is also developed to improve the query results and allows users to find clothing image of more preferred design. A series of experiments are conducted to test the qualities of the feature extraction methods and validate the effectiveness and efficiency of the RF-OPF prototype from multiple aspects. The evaluation scores of initial query results are used to test the qualities of the feature extraction methods. The average scores of all RF steps, the average numbers of RF iterations taken before achieving desired results and the score transition of RF iterations are used to validate the effectiveness and efficiency of the proposed RF-OPF prototype.

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Section: Introductionmentioning

confidence: 55%

Section: Methodsmentioning

confidence: 91%

Section: Methodsmentioning

confidence: 93%

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