Toward Improving Image Retrieval via Global Saliency Weighted Feature
نویسندگان
چکیده
منابع مشابه
Improving Query Expansion for Image Retrieval via Saliency and Picturability
In this paper, we present a Wikipedia-based approach to query expansion for the task of image retrieval, by combining salient encyclopaedic concepts with the picturability of words. Our model generates the expanded query terms in a definite two-stage process instead of multiple iterative passes, requires no manual feedback, and is completely unsupervised. Preliminary results show that our propo...
متن کاملFeature Selection Using Visual Saliency for Content-Based Image Retrieval
Saliency algorithms in content-based image retrieval are employed to retrieve the most important regions of an image with the idea that these regions hold the essence of representative information. Such regions are then typically analysed and described for future retrieval/classification tasks rather than the entire image itself thus minimising computational resources required. We show that we ...
متن کاملImage alignment via kernelized feature learning
Machine learning is an application of artificial intelligence that is able to automatically learn and improve from experience without being explicitly programmed. The primary assumption for most of the machine learning algorithms is that the training set (source domain) and the test set (target domain) follow from the same probability distribution. However, in most of the real-world application...
متن کاملEnhanced and Efficient Image Retrieval via Saliency Feature and Visual Attention
263 Abstract—In the real world applications such as landmark search, copy protection, fake image detection, partial duplicate image retrieval is very important. In the internet era users regularly upload images which are partially duplicate images on the domains like facebook, instagram and whatsapp etc. The partial image is only part of whole image, and the various kind of transformation invol...
متن کاملHierarchical Geometry Verification via Maximum Entropy Saliency in Image Retrieval
We propose a new geometric verification method in image retrieval—Hierarchical Geometry Verification via Maximum Entropy Saliency (HGV)—which aims at filtering the redundant matches and remaining the information of retrieval target in images which is partly out of the salient regions with hierarchical saliency and also fully exploring the geometric context of all visual words in images. First o...
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: ISPRS International Journal of Geo-Information
سال: 2021
ISSN: 2220-9964
DOI: 10.3390/ijgi10040249