Image-Based Pose Estimation for 3-D Modeling in Rapid, Hand-Held Motion

Abstract

This work aims at accurate estimation of the pose of a close-range 3-D modeling device in real-time, at high-rate, and solely from its own images. In doing so, we replace external positioning systems that constrain the system in size, mobility, accuracy, and cost. At close range, accurate pose tracking from image features is hard because feature projections do not only drift in the face of rotation but also in the face of translation. Large, unknown feature drifts may impede real-time feature tracking and subsequent pose estimation---especially with concurrent operation of other 3-D sensors on the same computer. The problem is solved in Ref. [1] by the partial integration of readings from a backing inertial measurement unit (IMU). In this work we avoid using an IMU by improved feature matching: full utilization of the current state estimation (including structure) <i>during</i> feature matching enables decisive modifications of the matching parameters for more efficient tracking---we hereby follow the Active Matching paradigm.