ShapeNets is an image representation, which is based on shape, compact structure, hierarchical image structure and appearance characteristic of object contour. In a ShapeNets, the shape of image is a window of containing objects which can be extracted with the method of objectness. The outline of objects can also be extracted in a line boundary detection algorithm based on histogram of gradients direction, which can be summarized by a representative node, and the relationship of spatial direction between objects can be described through the adaptive sampling granularity model. As a hierarchical structure, ShapeNets is from coarse to fine. The user can search the desired shape on the target image, and the system automatically inquires the image library, finding candidate regions of compatible semantic meaning. Finally, ShapeNets can help to achieve querying, matching, representation and some other functions.
['Hui Fan', 'Yan Zhang', 'Zhen Hua', 'Jinjiang Li', 'Sun Tz', 'Menglin Ren']
ShapeNets: Image Representation Based on the Shape