Action Recognition Using Low-Rank Sparse Representation

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

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

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Low-Rank and Eigenface Based Sparse Representation for Face Recognition

In this paper, based on low-rank representation and eigenface extraction, we present an improvement to the well known Sparse Representation based Classification (SRC). Firstly, the low-rank images of the face images of each individual in training subset are extracted by the Robust Principal Component Analysis (Robust PCA) to alleviate the influence of noises (e.g., illumination difference and o...

متن کامل

Robust face recognition via low-rank sparse representation-based classification

Face recognition has attracted great interest due to its importance in many real-world applications. In this paper, we present a novel low-rank sparse representation-based classification (LRSRC) method for robust face recognition. Given a set of test samples, LRSRC seeks the lowest-rank and sparsest representation matrix over all training samples. Since low-rank model can reveal the subspace st...

متن کامل

Complex event recognition using constrained low-rank representation

a r t i c l e i n f o Complex event recognition is the problem of recognizing events in long and unconstrained videos. In this extremely challenging task, concepts have recently shown a promising direction where core low-level events (referred to as concepts) are annotated and modeled using a portion of the training data, then each complex event is described using concept scores, which are feat...

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

human action recognition based on discriminative sparse representation on multi-manifolds

human action recognition is an important problem in computer vision. one of the methods that are recently used is sparse coding. conventional sparse coding algorithms learn dictionaries and codes in an unsupervised manner and neglect class information that is available in the training set. but in this paper for solving this problem, we use a discriminative sparse code based on multi-manifolds. ...

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

ژورنال

عنوان ژورنال: IEICE Transactions on Information and Systems

سال: 2018

ISSN: 0916-8532,1745-1361

DOI: 10.1587/transinf.2017edl8176