Filtering Method for Pose Angles Based on CS-STF-IMM

Abstract:

In order to decrease the error of pose estimation based on image sequences, a filtering method for pose angles based on CS-STF-IMM was proposed. Firstly, current statistical (CS) model was used to establish state space model of pose transformation, which reflects the maneuver of target pose more truly. Then, strong tracking filter (STF) was introduced to overcome the shortcoming that Kalman filter can hardly track sudden maneuver. A parameters determination method based on least square fitting was proposed, which improves the performance of STF further. Based on these, CS-STF-IMM algorithm was established, which obviously improved the precision of pose estimation. Simulations showed that the proposed method has better overall performance, which is a feasible scheme for pose angles filtering.

• Periodical: Advanced Materials Research (Volumes 457-458)
• Pages: 1271-1277
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.457-458.1271
• Online since: January 2012
• Authors: Bing Ji, Gan Lin Shan
• Keywords: Current Statistical Model, IMM, Pose Filtering, Strong Tracking Filter

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