Appearance-based tracking and recognition using the 3D trilinear tensor

Jie Shao, Shaohua Kevin Zhou, Rama Chellappa

Abstract: The paper presents an appearance-based adaptive algorithm for simultaneous tracking and recognition by generalizing the transformation model to 3D perspective transformation. A trilinear tensor operator is used to represent the 3D geometrical structure. The tensor is estimated by predicting the corresponding points using the existing affine-transformation based algorithm. The estimated tensor is used to synthesize novel views to update the appearance templates. Some experimental results using airborne video are presented.