Difference: PhysicsTracking (8 vs. 9)

Contribution: The authors present a model for people tracking, the Anthropomorphic Walker, that uses a low-dimensional dynamic controller to inform a physically realistic prediction of a person's pose and motion from source video. The predicted motions avoid several errors associated with purely kinematic solutions, such as footskate, implausible whole-body rotations, and discontinuous accelerations of the person.

Evaluation: The paper includes the trajectory tracking results for four different experimental clips. The experiments were made to demonstrate performance in spite of complications such as changing walking speed, occlusion of the walker, and a changing walking direction. They additionally determined the error of their tracker on part of the HumanEva data set, which includes ground truth motion capture data alongside the test video.

Reproducibility: The authors provide source code and results that demonstrate their chosen optimal control values given a step length and walking speed. Additionally, they provide explicit parameter values used in their system. As such, the paper's methodology should be reproducible.

Improvements:

• What justification exists for using a very simple 2D dynamic system with low-dimensional control to inform the 3D kinematic model? Would adding more control parameters to the dynamic model increase tracking accuracy?
• Section 5 (Sequential Monte Carlo Tracking) delves fairly deeply into symbolic math and can be confusing, especially for somebody not familiar with optical flow and this technique. It would have been appreciated to have an occasionally surface-for-air that gave motivation for each equation in terms of the final desired result.

-- BenHumberston - 01 Dec 2011

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