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Scene detection is a fundamental tool for allowing effective video browsing and re-using. In this paper we present a model that automatically divides videos into coherent scenes, which is based on a novel combination of local image descriptors and temporal clustering techniques. Experiments are performed to demonstrate the effectiveness of our approach, by comparing our algorithm against two recent...
We propose a novel approach for unsupervised visual domain adaptation that exploits auxiliary information in a target domain. The key idea is to embed data in the target domain into a subspace where samples are better organized, expecting auxiliary information to serve as a somewhat semantically related signal. Specifically, we apply partial least squares (PLS) to RGB image features and corresponding...
Unlike traditional multimedia content, content generated on social media platforms such as YouTube, Flickr etc are usually annotated with rich set of social tags such as keywords, textual description, category information, author's profile etc. In this paper we investigate the use of such social tag information for visual diversification of image search results in Flickr. We model search result diversity...
In this study, we present a system for video event classification that generates a temporal pyramid of static visual semantics using minimum-value, maximum-value, and average-value aggregation techniques. Kernel optimization and model subspace boosting are then applied to customize the pyramid for each event. SVM models are independently trained for each level in the pyramid using kernel selection...
This paper proposes a strategy to interactively explore large collections of images. The strategy is based on kernel methods, which offer a mathematically strong framework to address each stage of an exploratory image collection system: image representation, similarity function calculation, summarization, visualization and exploration. This work also proposes a dual form of the well-known Rocchio's...
Measuring image similarity is an important task for various multimedia applications. Similarity can be defined at two levels: at the syntactic (lower, context-free) level and at the semantic (higher, contextual) level. As long as one deals with the syntactic level, defining and measuring similarity is a relatively straightforward task, but as soon as one starts dealing with the semantic similarity,...
Visual target classification is one of the most important issues addressed in wireless multimedia sensor network (WMSN). This paper proposes a hybrid Gaussian process based classification method to implement binary visual classification (human/nonhuman) in WMSN. Because the computation ability of sensor node in WMSN is strictly limited, target classification is achieved by Gaussian process classifier...
It has been shown by researchers that using a multimodality approach can help in identifying better clusters in an image collection. The multimodal image features include low-level image features and available text annotations. This approach helps in identifying inherent relationships among different types of features associated with an image. In our approach, we divide images into small tiles and...
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