Object Counting Based on Its Panoramic Image Representation
Tzu-Chieh Chu, Fay Huang · 2019
This paper proposes a new object representation using a panoramic image and addresses a SIFT-based matching approach for counting the number of this object in an image. The proposed object panoramic image records the texture information of the object from all (360- degree) directions. Using it as a reference for finding the same object in another image involves the task of feature matching between a cylindrical panoramic and a planar view of the object. The main advantage of using this object representation is that it is possible to derive the orientation information of the detected object in the image. Preliminary experiments were conducted to verify the proposed algorithm.