ICA Based Face Recognition Robust to Partial Occlusions and Local Distortions

نویسندگان

  • Jongsun Kim
  • Jongmoo Choi
  • Juneho Yi
چکیده

We propose a novel method using a perfectly local facial representation based on ICA. We named our method “LS-ICA method”. In the LS-ICA method, basis images are made from their corresponding ICA basis images simply by removing non-salient regions. The LS-ICA basis images display perfectly local characteristics because they contain only locally salient feature regions. This enables us to effectively realize the idea of “recognition by parts” for face recognition. Experimental results using AT&T, Harvard, FERET and AR databases show that the recognition performance of the LS-ICA method outperforms that of PCA and ICA methods especially in the cases of facial images that have partial occlusions and local distortions such as changes in facial expression and at low dimensions.

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

Robust Face Recognition Based on Part-Based Localized Basis Images

In order for a subspace projection based method to be robust to local distortion and partial occlusion, the basis images generated by the method should exhibit a part-based local representation. We propose an effective partbased local representation method using ICA architecture I basis images that is robust to local distortion and partial occlusion. The proposed representation only employs loc...

متن کامل

Face Recognition Based on Locally Salient ICA Information

ICA (Independent Component Analysis) is contrasted with PCA (Principal Component Analysis) in that ICA basis images are spatially localized, highlighting salient feature regions corresponding to eyes, eye brows, nose and lips. However, ICA basis images do not display perfectly local characteristic in the sense that pixels that do not belong to locally salient feature regions still have some wei...

متن کامل

Face Recognition Using Pca, Lda and Ica Approaches on Colored Images

In this paper, the performances of appearance-based statistical methods such as Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and Independent Component Analysis (ICA) are tested and compared for the recognition of colored face images. Three sets of experiments are conducted for relative performance evaluations. In the first set of experiments, the recognition performanc...

متن کامل

Kernel sparse representation with pixel-level and region-level local feature kernels for face recognition

Face recognition has been popular in pattern recognition field for decades, but it is still a difficult problem due to the various image distortions. Recently, Sparse Representation based Classification (SRC) was proposed as a novel image classification approach, which is very effective with sufficient training samples for each class. However, the performance drops when the number of training s...

متن کامل

Robust feature set matching for partial face recognition

Various approaches have been proposed to recognize complete faces. However, few have dealt with the problem of recognizing an arbitrary partial face. In real-world scenarios, human faces might easily be occluded by other objects. This made traditional face recognition algorithms, which heavily rely on face alignment and face normalization, infeasible. In this paper, we propose a partial face re...

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 2004