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Region labelling using a Point-Based Coherence Criterion

机译:使用基于点的相干性准则标记区域

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Query By Visual Example (QBVE) has been widely exploited in image retrieval. Global visual similarity as well as points of interest matching have proven their efficiency when example image/region is available. If starting image is missing, the Query By Visual Thesaurus (QBVT) paradigm offsets it by allowing the user to compose his mental query image through visual patches summarizing the region database. In this paper, we propose to enrich the paradigm of mental image search by constructing a reliable visual thesaurus of the regions provided by a new coherence criterion. Our criterion encapsulates the local distribution of detected points of interest within a region. It leads to semantic labelling of regions categories using points spatial topology. Our point-based criterion has been validated on a generic image database combining homogenous regions as well as irregularly and fully textured patterns.
机译:通过可视示例查询(QBVE)已在图像检索中得到广泛利用。当示例图像/区域可用时,全局视觉相似度以及兴趣点匹配已证明其效率。如果缺少起始图像,则“通过视觉词库查询(QBVT)”查询范式通过允许用户通过汇总区域数据库的可视补丁来构成其心理查询图像来抵消它。在本文中,我们建议通过构建由新的连贯性准则提供的区域的可靠视觉同义词库来丰富心理图像搜索的范式。我们的标准封装了区域内检测到的兴趣点的局部分布。它导致使用点空间拓扑对区域类别进行语义标记。我们的基于点的标准已在包含均匀区域以及不规则和完全纹理图案的通用图像数据库中得到验证。

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