Hand tracking in a natural conversational environment by the interacting multiple model and probabilistic data association (IMM-PDA) algorithm
| Autor: | Shunguang Wu, Lang Hong |
|---|---|
| Rok vydání: | 2005 |
| Předmět: |
Computer science
business.industry Probabilistic logic Process (computing) Joint Probabilistic Data Association Filter Kalman filter Set (abstract data type) Acceleration Artificial Intelligence Signal Processing Clutter Computer vision Computer Vision and Pattern Recognition Artificial intelligence Noise (video) business Algorithm Software |
| Zdroj: | Pattern Recognition. 38:2143-2158 |
| ISSN: | 0031-3203 |
| DOI: | 10.1016/j.patcog.2005.01.020 |
| Popis: | Traditional image based hand tracking algorithms use a single model Kalman filter to estimate and predict the hand state (position, velocity, and acceleration) and do not consider multiple measurements with noise and false alarms. However, these approaches may fail in the case of large maneuvers and/or a clutter measurement environment. In this paper, we apply the interacting multiple model (IMM) to catch hand maneuvers and the probabilistic data association (PDA) method to process noisy measurements and false alarms. A theoretical framework of image based hand tracking by the IMM-PDA algorithm is set up. Experiment results from several long video segments show that the IMM-PDA algorithm gives a superior performance compared to single model based Kalman filters. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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