ComMon SensE: Cross-Modal Search Engine
STATUS: TEST PHASE This demo may be unstable…
The CMSE is our initiative to develop a framework for cross-modal multimedia search.
The CMSE is first a feature extraction library. Based on the OpenCV framework, it is able to process images of any type and extract many features related to
- Color
- Texture
- Edges
- Faces
- …
The CMSE also accounts for the textual modality and indexes it as the classical bags-of-words.
The CMSE is then an indexing engine built around our defined indexing and retrieval strategies (see references below).
Some references (see also our list of publications)
- Bruno, É., Moënne-Loccoz, N., & Marchand-Maillet, S. (2008). Design of multimodal dissimilarity spaces for retrieval of multimedia documents. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(9), 1520-1533.
- Kludas, J., Bruno, E., & Marchand-Maillet, S. (2008). Can Feature Information Interaction help for Information Fusion in Multimedia Problems?. To appear in Multimedia Tools and Applications Journal special issue on “Metadata Mining for Image Understanding”.
- Bruno, E., Kludas, J., & Marchand-Maillet, S. (2007). Combining Multimodal Preferences for Multimedia Information Retrieval. In Proc. of International Workshop on Multimedia Information Retrieval, Augsburg, Germany.