Object Localization in Metric Spaces for Video Linking
| Type of publication: | Conference paper |
| Citation: | gatica03b-conf |
| Booktitle: | IEEE Workshop on Motion and Video Computing |
| Year: | 2002 |
| Crossref: | gatica03b: |
| Abstract: | While objects often constitute the desired level of access for browsing and retrieval in video databases, an inherent problem for on-line object definition is that of model construction from a few examples. In this paper, we present a probabilistic methodology to localize objects that appear across video segments, based on video structuring, object definition, and localization in the video structure. Localization is formulated as a problem of random sampling in a Metric Mixture Model framework, which allows for the joint modeling of a set of color appearance exemplars and their geometric transformations. To improve the efficiency of the sampling process, candidate configurations are drawn from a prior distribution using importance sampling, and evaluated using Bayes' rule. Experimental results on a database extracted from home videos depicting real objects (with variations of scale and pose) across video shots show the performance of the method. |
| Userfields: | ipdmembership={vision}, |
| Keywords: | |
| Projects |
Idiap |
| Authors | |
| Added by: | [UNK] |
| Total mark: | 0 |
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