Saliency Detection Using Sparse and Nonlinear Feature Representation
نویسندگان
چکیده
منابع مشابه
Saliency Detection Using Sparse and Nonlinear Feature Representation
An important aspect of visual saliency detection is how features that form an input image are represented. A popular theory supports sparse feature representation, an image being represented with a basis dictionary having sparse weighting coefficient. Another method uses a nonlinear combination of image features for representation. In our work, we combine the two methods and propose a scheme th...
متن کاملAn Image Sparse Representation for Saliency Detection
This paper presents a novel method for detecting saliency in static images based on image sparse representation. For each color channel, first, the image is partitioned into non-overlapping patches and each patch is represented by the way of sparse coding from a learned dictionary of patches from natural scenes. Then, global saliency and local saliency are calculated and fused to attain salienc...
متن کاملFeature Selection and Pedestrian Detection Based on Sparse Representation
Pedestrian detection have been currently devoted to the extraction of effective pedestrian features, which has become one of the obstacles in pedestrian detection application according to the variety of pedestrian features and their large dimension. Based on the theoretical analysis of six frequently-used features, SIFT, SURF, Haar, HOG, LBP and LSS, and their comparison with experimental resul...
متن کاملAbnormal Activity Detection Using Spatio-Temporal Feature and Laplacian Sparse Representation
Abnormal activity detection in a video is a challenging and attractive task. In this paper, an approach using spatio-temporal feature and Laplacian sparse representation is proposed to tackle this problem. To detect the abnormal activity, we first detect interest points of a query video in the spatio-temporal domain. Then normalized combinational vectors, named HNF, are computed around the dete...
متن کاملMultifocus Image Fusion Using Sparse Representation by Adaptive Feature Matching
Optical imaging cameras suffer from the problem of limited depth-of-field of optical lenses, so it is difficult to get an image with all objects in focus. One way to overcome this problem is by using multi-focus image fusion technique, in which several images with different focus points are combined to form a single image with all objects fully focused. So, it is crucial to effectively extract ...
متن کاملذخیره 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: The Scientific World Journal
سال: 2014
ISSN: 2356-6140,1537-744X
DOI: 10.1155/2014/137349