Search Results

With the growth of images on the Internet, plenty of hashing methods are developed to handle the large-scale image retrieval task. Hashing methods map data from high dimension to compact codes, so that they can effectively cope with complicated image ...

Online Social Network Sites have become a primary platform for brands and organizations to engage their audience by sharing image and video posts on their timelines. Different from traditional advertising, these posts are not restricted to the products ...

In natural images, it remains challenging to estimate dissimilarities between image elements for scene representation due to gradual variations of illuminations, textures or clutters. To tackle this problem, we utilise a path‐based bottleneck analysis ...

Brands and organizations are using social networks such as Instagram to share image or video posts regularly, in order to engage and maximize their presence to the users. Differently from the traditional advertising paradigm, these posts feature not ...

With mobile devices, users are taking ever-growing numbers of photos every day. These photos are uploaded to social sites such as Facebook and Flickr, often automatically. Yet, the portion of these uploaded photos being publicly shared is low, and on a ...

The Distance Metric Learning (DML) has been in attentive on image retrieval, but many of the previous methods are used for classification and clustering of the images. In this paper, we are focusing on designing the ordinal DML algorithms for image ...

Human computation is a very powerful tool for solving tasks that cannot be solved by computers efficiently. One such problem is ranking images upon their relevance for a semantic query or upon how well they depict a semantic concept. In this paper we ...

Although Web search techniques have greatly facilitate users’ information seeking, there are still quite a lot of search sessions that cannot provide satisfactory results, which are more serious in Web image search scenarios. How to understand user ...

Recently, the visual attribute of images is becoming a research focus in computer vision and multimedia retrieval areas due to its describable or human-nameable nature for image understanding. In this paper, the visual attribute is utilized to boost the ...

Searching for images on-line using keywords returns results that are often difficult to interpret. This becomes even more complicated if one attempts to compare image search output for several keywords with a common theme. We focus on the latter problem ...

Ranking of images is difficult because many factors determine their importance (e.g., popularity, quality, entertainment value, context, etc.). In social media platforms, ranking also depends on social interactions and on the visibility of the images ...

Learning to rank has been demonstrated as a powerful tool for image ranking, but the issue of the "curse of dimensionality" is a key challenge of learning a ranking model from a large image database. This paper proposes a novel dimensionality reduction ...

Recently, the field of CBIR has attracted a lot of attention in the literature. In this paper, the problem of visually similar image retrieval has been investigated. For this task we use the methods derived from the Bag of Visual Words approach, such as ...

In this paper, we present a novel algorithm called manifold ordinal regression (MOR) for image ranking. By modeling the manifold information in the objective function, MOR is capable of uncovering the intrinsically nonlinear structure held by the image ...

We propose a novel approach for ranking and retrieval of images based on multi-attribute queries. Existing image retrieval methods train separate classifiers for each word and heuristically combine their outputs for retrieving multiword queries. ...

Video retrieval through text queries is a very common practice in broadcaster archives. The query keywords are compared to the metadata labels that documentalists have previously associated to the video assets. This paper focuses on a ranking strategy ...

With the explosive growth of digital cameras and online media, it has become crucial to design efficient methods that help users browse and search large image collections. The recent VisualRank algorithm [4] employs visual similarity to represent the ...

Searching for relevant images given a query term is an important task in nowadays large-scale community databases. The image ranking approach presented in this work represents an image collection as a graph that is built using a multimodal similarity ...

In this paper, we investigate the influence of facial parameters on the subjective impression that is created when looking at photographs containing people in the context of keyframe extraction from home video. Hypotheses about the influence of ...