مشخصات پژوهش

عنوان	Knowledge-Based Semantic Image Segmentation Based on Global Precedence Effect
نوع پژوهش	مقاله ارائه شده کنفرانسی
کلیدواژه‌ها	Knowledge Based-Semantic Image Segmentation-Global Precedence Effect
چکیده	This paper introduces a knowledge-based semantic image segmentation which extracts the “object(s)-of-interest” from the image. Image templates are the high-level knowledge in the system. The major contribution of this work is the use of the “Global Precedence Effect” (forest before trees) of the human visual system (HVS) in image analysis and understanding. The “object-of-interest” is searched for hierarchically through an irregular pyramid by an affine invariant comparison between the different region combinations and the template starting from lowest to the highest resolutions. The global/large size objects are found at lower resolutions with significantly lower computational complexity.
پژوهشگران	گولشاه نقدی (نفر دوم)، فردین اخلاقیان طاب (نفر اول)