کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
380602 1437448 2014 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A highly accurate dense approach for homography estimation using modified differential evolution
ترجمه فارسی عنوان
یک رویکرد متراکم دقیق برای برآورد همگرافی با استفاده از تفاضل تفاضلی اصلاح شده
کلمات کلیدی
برآورد همگرا، تکامل دیفرانسیل، جستجو درشت به خوب، مطابقت تصویر
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی


• Two-objective optimization problem formulation for homography estimation.
• Fast pre-evaluation test which discards invalid solution at an early stage.
• C2F strategy integrated in proposed framework leads to significant speedup.
• Quantitative evaluation of the new method using data with ground truth.
• Qualitative evaluation of the new method in two real-world applications.

The homography corresponds to a 3×3 matrix which transfers image points between two images of a planar scene or two images captured by cameras under purely rotational motion. Homography estimation is crucial to many computer vision tasks involving multi-view geometry. Unlike most existing algorithms using sparse information extracted from images, this paper proposes a dense homography estimation method taking into account both the color and gradient information of the whole image. In particular, homography estimation is recast as a two-objective optimization problem, which is solved within a global optimization procedure guided by sparse control points (SCPs) based on modified differential evolution (DE). In order to improve the computational efficiency, two strategies namely pre-evaluation and coarse-to-fine (C2F) search are integrated into the proposed framework. The experimental results on synthetically rendered images and real images demonstrate that the new method can consistently improve the accuracy of homography estimation compared with two most successful feature based algorithms, and the incorporated acceleration strategies are able to speed up the minimization procedure by about 15 times. The applicability of our proposed method is further demonstrated in two real-world applications, namely occlusion removal and image mosaicing.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Engineering Applications of Artificial Intelligence - Volume 31, May 2014, Pages 68–77
نویسندگان
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