On the significance of cluster-temporal browsing for generic video retrieval

Rautiainen, Mika; Seppänen, Tapio; Ojala, Timo

doi:10.1145/1180639.1180676

Cited by 2 publications

(3 citation statements)

References 6 publications

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“…To ensure that users mark shots correctly they have to be able to access the timeline, which is indeed shown to be important for video retrieval [Rautiainen et al 2006;Adcock et al 2005;Christel et al 2004;Snoek et al 2007]. …”

Section: Inspection Phasementioning

confidence: 99%

Efficient targeted search using a focus and context video browser

Rooij

Worring

2012

ACM Trans. Multimedia Comput. Commun. Appl.

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Currently there are several interactive content-based video retrieval techniques and systems available. However, retrieval performance depends heavily on the means of interaction. We argue that effective CBVR requires efficient, specialized user interfaces. In this article we propose guidelines for such an interface, and we propose an effective CBVR engine: the ForkBrowser, which builds upon the principle of focus and context. This browser is evaluated using a combination of user simulation and real user evaluation. Results indicate that the ideas have merit, and that the browser performs very well when compared to the state-of-the-art in video retrieval.

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Section: Inspection Phasementioning

confidence: 99%

Efficient targeted search using a focus and context video browser

Rooij

Worring

2012

ACM Trans. Multimedia Comput. Commun. Appl.

View full text Add to dashboard Cite

show abstract

“…In semantic video retrieval, the performance measure of choice is average precision [1], [14]. For a ranked list of elements, average precision denotes the area under the precision recall graph.…”

Section: Performance Estimation Between Unbalanced Setsmentioning

confidence: 99%

“…However, optimizing the AUC does not guarantee to optimize average precision [16]. Other performance measures like R-precision [17], normalized average rank [18], normalized average precision [14], inferred average precision [19], or interpolated precision [20] may optimize average precision; however, they do not scale between a fixed minimum and maximum. To the best of our knowledge, no performance measure exists that satisfies our demands.…”

Section: Performance Estimation Between Unbalanced Setsmentioning

confidence: 99%