• multiscale symmetric part detection and grouping

    جزئیات بیشتر مقاله
    • تاریخ ارائه: 1392/07/24
    • تاریخ انتشار در تی پی بین: 1392/07/24
    • تعداد بازدید: 1187
    • تعداد پرسش و پاسخ ها: 0
    • شماره تماس دبیرخانه رویداد: -
     skeletonization algorithms typically decompose an object’s silhouette into a set of symmetric parts, offering a powerful representation for shape categorization. however, having access to an object’s silhouette assumes correct figure-ground segmentation, leading to a disconnect with the mainstream categorization community, which attempts to recognize objects from cluttered images. in this paper, we present a novel approach to recovering and grouping the symmetric parts of an object from a cluttered scene. we begin by using a multiresolution superpixel segmentation to generate medial point hypotheses, and use a learned affinity function to perceptually group nearby medial points likely to belong to the same medial branch. in the next stage, we learn higher granularity affinity functions to group the resulting medial branches likely to belong to the same object. the resulting framework yields a skeletal approximation that is free of many of the instabilities that occur with traditional skeletons. more importantly, it does not require a closed contour, enabling the application of skeleton-based categorization systems to more realistic imagery.

سوال خود را در مورد این مقاله مطرح نمایید :

با انتخاب دکمه ثبت پرسش، موافقت خود را با قوانین انتشار محتوا در وبسایت تی پی بین اعلام می کنم
مقالات جدیدترین ژورنال ها