Face Recognition with Image Misalignment via Structure Constraint Coding

نویسندگان

  • Ying Tai
  • Jianjun Qian
  • Jian Yang
  • Zhong Jin
چکیده

Face recognition (FR) via sparse representation has been widely studied in the past several years. Recently many sparse representation based face recognition methods with simultaneous misalignment were proposed and showed interesting results. In this paper, we present a novel method called structure constraint coding (SCC) for face recognition with image misalignment. Unlike those sparse representation based methods, our method does image alignment and image representation via structure constraint based regression simultaneously. Here, we use the nuclear norm as a structure constraint criterion to characterize the error image. Compared with the sparse representation based methods, SCC is more robust for dealing with illumination variations and structural noise (especially block occlusion). Experimental results on public face databases verify the effectiveness of our method.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Face Recognition using an Affine Sparse Coding approach

Sparse coding is an unsupervised method which learns a set of over-complete bases to represent data such as image and video. Sparse coding has increasing attraction for image classification applications in recent years. But in the cases where we have some similar images from different classes, such as face recognition applications, different images may be classified into the same class, and hen...

متن کامل

Face Recognition Using Sparse Representation

Many classic and contemporary face recognition algorithms work well on public data sets, but degrade sharply when they are used in a real recognition system. This is mostly due to the difficulty of simultaneously handling variations in illumination, image misalignment, and occlusion in the test image. We consider a scenario where the training images are well controlled and test images are only ...

متن کامل

Robust and Practical Face Recognition via Structured Sparsity

Sparse representation based classification (SRC) methods have recently drawn much attention in face recognition, due to their good performance and robustness against misalignment, illumination variation, and occlusion. They assume the errors caused by image variations can be modeled as pixel-wisely sparse. However, in many practical scenarios these errors are not truly pixel-wisely sparse but r...

متن کامل

A new Sparse Coding Approach for Human Face and Action Recognition

Sparse coding is an unsupervised method which learns a set of over-complete bases to represent data such as image, video and etc. In the cases where we have some similar images from the different classes, using the sparse coding method the images may be classified into the same class and devalue classification performance. In this paper, we propose an Affine Graph Regularized Sparse Coding appr...

متن کامل

Automatic Face Recognition via Local Directional Patterns

Automatic facial recognition has many potential applications in different areas of humancomputer interaction. However, they are not yet fully realized due to the lack of an effectivefacial feature descriptor. In this paper, we present a new appearance based feature descriptor,the local directional pattern (LDP), to represent facial geometry and analyze its performance inrecognition. An LDP feat...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2014