tailieunhanh - Báo cáo toán học: " Automated target tracking and recognition using coupled view and identity manifolds for shape representation"

Tuyển tập các báo cáo nghiên cứu khoa học ngành toán học được đăng trên tạp chí toán học quốc tế đề tài: Automated target tracking and recognition using coupled view and identity manifolds for shape representation | Venkataraman et al. EURASIP Journal on Advances in Signal Processing 2011 2011 124 http content 2011 1 124 o EURASIP Journal on Advances in Signal Processing a SpringerOpen Journal RESEARCH Open Access Automated target tracking and recognition using coupled view and identity manifolds for shape representation Vijay Venkataraman 1 Guoliang Fan1 Liangjiang Yu1 Xin Zhang2 Weiguang Liu3 and Joseph P Havlicek4 Abstract We propose a new couplet of identity and view manifolds for multi-view shape modeling that is applied to automated target tracking and recognition ATR . The identity manifold captures both inter-class and intra-class variability of target shapes while a hemispherical view manifold is involved to account for the variability of viewpoints. Combining these two manifolds via a non-linear tensor decomposition gives rise to a new target generative model that can be learned from a small training set. Not only can this model deal with arbitrary view pose variations by traveling along the view manifold it can also interpolate the shape of an unknown target along the identity manifold. The proposed model is tested against the recently released SENSIAC ATR database and the experimental results validate its efficacy both qualitatively and quantitatively. Keywords tracking and recognition shape representation shape interpolation manifold learning 1 Introduction Automated target tracking and recognition ATR is an important capability in many military and civilian applications. In this work we mainly focus on tracking and recognition techniques for infrared IR imagery which is a preferred imaging modality for most military applications. A major challenge in vision-based ATR is how to cope with the variations of target appearances due to different viewpoints and underlying 3D structures. Both factors identity in particular are usually represented by discrete variables in practical existing ATR algorithms 1-3 . In this paper we will account for .