Adaptive particle filter based pose estimation using a monocular camera model

Abstract

Camera full pose estimation using only a monocular camera model is an important topic in the field of visual servoing. In this paper a simple adaptive method for updating the weights of particle filter is proposed. Using this method, the efficiency of particle filter in estimating the full pose of camera is improved. Results of the proposed method are compared with those of generic particle filter (PF) and EKF under the same condition through an intensive computer simulation.

Machine-Vision-Based Pose Estimation System Using Sensor Fusion for Autonomous Satellite Grappling

“…Edges/Pixels/Gradient (images) [18], [19], [20], [21], [22]* Feature Extraction Points [23], [24], [25]* Lines [7]* Multiple Features [26], [27], [28] Feature Based Points [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56]*, [8]*, [57]*, [58], [59] Lines [60], [61], [62], [63], [64], [65]...…”