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Physics-based Person Tracking Using the Anthropomorphic Walker | ||||||||
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The paper is well-organized and the results are presented in a way that's easy to understand and appreciate. I found the formulas to be confusing however, usually because it wasn't entirely obvious what each symbol being used meant. Referring back to the reproducibility of the paper, I also feel the paper would benefit from additional detail on some of the algorithms and tools used to implement their system. -- Main.cdoran - 01 Dec 2011 | ||||||||
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Contribution: The study proposes a physics-based model for 3D tracking of a person from monocular video sequences. The presented model applies a probabilistic approach and it exploits basic physical principles in the design of a prior density model over human motion. It also uses a low-dimensional, biomechanically inspired models. As a result, it achieves crucial characteristics of bipedal locomotion such as balance and ground contact. Moreover, the model aims for reducing the dependence of models on mocap data which in turn enable models to generalize to different styles, such as varying walking speed, step length, and mass, as well as avoiding some of the problems of other approaches, e.g. footstake. Evaluation: The study includes four experiments for evaluating the accuracy and the generalization capabilities of the proposed model. Experiment 1 and 3 demonstrates the genralization of the model across different walking speeds, and motions styles, such as turning. Experiment 2 shows the robustness of the method as it can still track a person even when there are occlusions. Lastly, fourth experiment supports the results by using the HumanEva dataset, as it quantitatively compares and assesses the tracking results with the ground truth. It turns out that estimating the depth information is, unsurprisingly, the hardest part of such a problem. Reproducibility: Even though the theoretical explanations are detailed out, most of the implementation details, as well as the hand-tuned parameters are left out from the paper. One has to look at the given reference papers for the implementation. On the other hand, they have released a version of their implementation, which would definitely be helpful to reproduce the results. Improvements: A possible improvement for that study would be to investigate possible controllers for generalizing over different morphologies, or even moods of characters. The paper is well-written, but it's not very easy to follow as it incorporates ideas/methods from different areas. -- Main.ooguz - 01 Dec 2011 | |||||||
-- MichielVanDePanne - 27 Nov 2011 |