Multi-Source Human ID
نویسندگان
چکیده
Motivation: Research in audio-visual speech recognition, eg. [1, 5] , shows that classification results can be improved by integrating evidence from multiple sources of observation. Similar results have been observed and demonstrated in verification systems, such as [6], as well as in multi-modal trackers, eg. [7]. In the area of human identification current state of the art systems deliver very high recognition rate in a single modality. In our project we extend the idea of multimodal cue integration to the domain of person identification.
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