Our paper on “Video Event Classification using String Kernels“ was accepted for publication by Springer International Journal on Multimedia Tools and Applications (MTAP) in the special issue on Content-Based Multimedia Indexing.
In this paper we present a method to introduce temporal information for video event recognition within the bag-of-words (BoW) approach. Events are modeled as a sequence composed of histograms of visual features, computed from each frame using the traditional BoW. The sequences are treated as strings phrases where each histogram is considered as a character. Event classification of these sequences of variable length, depending on the duration of the video clips, are performed using SVM classifiers with a string kernel that uses the Needlemann-Wunsch edit distance.
Our paper on “Semantic annotation of soccer videos by visual instance clustering and spatial/temporal reasoning in ontologies” was accepted for publication by Springer International Journal on Multimedia Tools and Applications (MTAP).
In this paper we present a framework for semantic annotation of soccer videos that exploits an ontology model referred to as Dynamic Pictorially Enriched Ontology, where the ontology, defined using OWL, includes both schema and data. Visual instances are used as matching references for the visual descriptors of the entities to be annotated. The paper is available online now and it is also available on SpringerLink in the “Online First” section (DOI).
Our ICIP 2009 and ICCV VOEC 2009 papers are available online. We are working at a novel method based on an effective visual bag-of-words model and on a new spatio-temporal descriptor.
First, we define a new 3D gradient descriptor that combined with optic flow outperforms the state-of-the-art, without requiring fine parameter tuning (ICIP paper).
Second, we show that for spatio-temporal features the popular k-means algorithm is insufficient because cluster centers are attracted by the denser regions of the sample distribution, providing a non-uniform description of the feature space and thus failing to code other informative regions. For this reason we use a radius-based clustering method and a soft assignment that considers the information of two or more relevant candidates, thus obtaining a more effective codebook (ICCV VOEC paper). We extensively test our approach on standard KTH and Weizmann action datasets showing its validity and outperforming other recent approaches.
We will host in Florence the 18th ACM International Conference on Multimedia (ACM MM). ACM Multimedia is the premier annual professional meeting for communicating the state-of-the-art in multimedia research, technology, and art.
ACM Multimedia 2010 will be held in Florence, Italy, on October 25-29, 2010.
Visit ACM Multimedia 2010 site.
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