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We present a crowdsourcing (CS) study to examine how specific attributes probabilistically affect the selection and sequencing of images from personal photo collections. Thirteen image attributes are explored, including seven people-centric properties. We first propose a novel dataset shaping technique based on mixed integer linear programming (MILP) to identify a subset of photos in which the attributes...
This paper presents PhotoCluster, a new technique for identifying non-identical near-duplicate images in personal photo collections. Contrary to existing methods, PhotoCluster estimates the probability that a pair of images may be considered near-duplicate. Its main thrust is a multiple clustering step that produces a non-binary near-duplicate probability for each image pair, which exhibits correlation...
The complexity of an image tells many aspects of the image content and is an important factor in the selection of source material for testing various image processing methods. We explore objective measures of complexity that are based on compression. We show that spatial information (SI) measures strongly correlate with compression-based complexity measures. Among the commonly used SI measures, the...
Managing photo collections involves a variety of image quality assessment tasks, e.g. the selection of the “best” photos. Detecting near-duplicate images is a prerequisite for automating these tasks. This paper presents a new dataset that may assist researchers in testing algorithms for the detection of near-duplicates in personal photo libraries. The proposed dataset is derived directly from an actual...
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