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Face based image navigation and search

Face based image navigation and search,10.1145/1631272.1631365,Tong Zhang,Jun Xiao,Di Wen,Xiaoqing Ding

Face based image navigation and search   (Citations: 10)
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People are often the most important subjects in photos, and the ability of finding photos of a particular person easily and quickly in an image collection is highly desired. In this paper, we present a face clustering system which automatically groups photos into clusters, with each cluster containing photos of the same person. This is done based on an advanced face recognition engine and a semi-supervised clustering approach. The system achieved good clustering accuracy when tested on different image sets and by different users. Moreover, features such as adding new images, face cluster navigation and face based image retrieval are added that greatly improve the usability of the system. It also facilitates efficient manual manipulations of clustering results. On top of this technology, image navigation systems have been built, including the "face bubble" visualization which provides one-glance view of a photo collection, and shows the relations among people.
Conference: ACM Multimedia Conference - MM , pp. 597-600, 2009
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    • ...In addition, a number of studies have actively utilized face annotations in personal photo systems [2, 3, 6]...

    Heung-Nam Kimet al. Photo search in a personal photo diary by drawing face position with p...

    • ...Based on state-of-the-art face recognition technology, we developed a face clustering algorithm in earlier work which automatically divides a photo collection into a number of clusters, with each cluster containing photos of one particular person [3]...

    Tong Zhanget al. Dynamic Estimation of Family Relations from Photos

    • ...By applying face clustering to images in the collection [3], photos of the same person are grouped together...

    Tong Zhang. Building dynamic relation tree from photo collections

    • ...On top of an advanced face recognition engine built in our prior work, we have developed a face clustering technology which automatically divides a photo collection into a number of clusters, with each cluster containing photos of one particular person [5, 6]. As the result, major clusters (that is, those having a relatively large number of photos) corresponding to frequently appearing people may be deemed as containing major characters of ...
    • ...10~20 years). More details can be found in [5] and [6]...
    • ...If user inputs are available, the clusters may be adjusted with operations such as merging and splitting [6], or even labeled with names...

    Tong Zhanget al. Consumer image retrieval by estimating relation tree from family photo...

    • ...Since the number of face clusters is unknown, we use agglomerate clustering method to automatically determine the number of clusters[9]...
    • ...We employ the K-nearest neighbor method described in [9] to measure the cluster level distance...

    Peng Wuet al. Improving face clustering using social context

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