鱼眼图像校正算法研究与实现

鱼眼镜头广泛应用于全景监控领域,本文介绍如何对鱼眼图像进行校正,并对特定角度下拍摄的鱼眼图像提出了一种简单、快速、实用性强的鱼眼图像校正方法,同时给出具体算法的推导,实验表明该方法能取得比较满意的效果.     

Interactive Evaluation of the Ostensive Model Using a New Test Collection of Images with Multiple Relevance Assessments

The Ostensive Model proposes a manner of structuring the uncertainty associated with individual relevance judgements as sources of evidence in relevance feedback. It proposes temporal profiles of uncertainty, motivating the application of a particular class of discount function with respect to the age of the evidence. This paper presents an initial evaluation of the relative effectiveness of different uncertainty discount functions.A novel direct manipulation interface to a multimedia retrieval system embodying the Ostensive Model is outlined briefly. The paper describes the construction and characteristics of a new image test collection utilising multiple binary relevance assessments. The use of such multiple assessments and multiple interpretations of them are discussed. The evaluation environment is detailed in terms of the interface, test collection, and tasks set to users. Multiple interpretations of the results, and the statistical significance of comparisons are presented.The results obtained in the evaluation are consistent with the proposals of the Ostensive Model—reinforcing a particular evidence profile. The results give clear pointers to further, more specific, evaluations.