On the Selection of Anchors and Targets for Video Hyperlinking
Zhi-Qi Cheng, Hao Zhang, Xiao Wu, Chong-Wah Ngo

TL;DR
This paper investigates how to select effective anchors and targets for video hyperlinking by analyzing data properties like hubness and intrinsic dimensionality, proposing algorithms to improve navigation and user experience.
Contribution
It introduces novel algorithms for automatic selection of anchors and targets based on hubness and local intrinsic dimensionality, addressing a key challenge in video hyperlinking.
Findings
Algorithms effectively identify meaningful anchors and targets
Selection reduces user frustration and improves navigation
Insights into data properties guide hyperlinking choices
Abstract
A problem not well understood in video hyperlinking is what qualifies a fragment as an anchor or target. Ideally, anchors provide good starting points for navigation, and targets supplement anchors with additional details while not distracting users with irrelevant, false and redundant information. The problem is not trivial for intertwining relationship between data characteristics and user expectation. Imagine that in a large dataset, there are clusters of fragments spreading over the feature space. The nature of each cluster can be described by its size (implying popularity) and structure (implying complexity). A principle way of hyperlinking can be carried out by picking centers of clusters as anchors and from there reach out to targets within or outside of clusters with consideration of neighborhood complexity. The question is which fragments should be selected either as anchors or…
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Taxonomy
TopicsAdvanced Image and Video Retrieval Techniques · Advanced Clustering Algorithms Research · Video Analysis and Summarization
