Abstract
The correspondence analysis part of a model based vision system is investigated theoretically and through a synthetic image sequence showing a human hand gesture. The purpose of the study is to find and describe ways of improving the conditions for robust tracking, by introducing a priori knowledge such as structural information from the model and temporal context of the observed motion.
Primary performance characteristics are the size of the search space for correspondence analysis, and the prediction error under various conditions.
Theoretical models for the search space dependencies on connectivity properties and on prediction accuracy are developed. Observations from the image sequence suggest simple predictors for the context of smooth motion, and their expected influence on search space is verified. Special considerations must be given to handling of motion trajectory discontinuities, and alternatives are suggested.
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© 1998 Springer-Verlag
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Munk, K.H., Granum, E. (1998). On the use of context and a priori knowledge in motion analysis for visual gesture recognition. In: Wachsmuth, I., Fröhlich, M. (eds) Gesture and Sign Language in Human-Computer Interaction. GW 1997. Lecture Notes in Computer Science, vol 1371. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0052994
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DOI: https://doi.org/10.1007/BFb0052994
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