Physics-based Person Tracking Using the Anthropomorphic Walker

Contribution:
Evaluation:
Reproducibility:
Improvements:

Contribution : Physics based Model for tracking people,as an alternative to other methods, for instance kinematic models, is suggested. Instead of modeling full body dynamics, a biomechanics based lower body tracking model is implemented.

Evaluation: The model was evaluated for 4 different types of walking and environmental variations. Three of these were generated specifically to test the model performance in changes in speed, simulated occlusion and turning. The model then was applied to an external dataset (HumanEva).

Reproducibility: The components of the model have been explained considerably well, though lots of the have been referred to previous work and weren't revisited. THe parameters of most of these components appeared to have been set manually or empirically while evaluation. So, there might stay some room for ambiguity while reproducing the results completely.

Improvements: Overall the paper was well written and explained. Model parameter selection could have been emphasized more.

-- Main.sumanm - 01 Dec 2011

Contribution: A new method for tracking is proposed, where the underlying model is not kinematic but rather physics-based. The method function without learning and is real time, but focuses mainly on walking, and the tracking is based on monocular video sequences.

Evaluation: I think this part was actually very good. The showed a very good visualization of their results vs reality by an overlaid image, and the carried out a variety of experiments (various speeds, etc) to show robustness. Some numerical values would have been perfection, but those are in general difficult to obtain.

Improvements: performance would probably be boosted by using more than one point of view. As it is, it seems they can only track movements that lie perfectly on a plane perpendicular to the direction of the camera, which while a good first step, is far from optimal.

Reproducibility: I think this is the part where the paper is most laking. While explicit formulas and algorithms are given and spelled out, parameters are not specified, nor are the conditions of the recording and so on. This paper is fairly complex and hard to describe with perfect accuracy, however, so the authors had to compromise between length and precision.

-- Main.ginestra - 01 Dec 2011

Contribution: The paper presents a method for tracking the locomotion of a human from single-camera video sequences. This is accomplished by first contructing a 2-dimensional physics-based model of lower-body locomotion called an Anthropomorphic Walker. This is used to form a generative model of a simplified 3-dimensional kinematic human body. These two components are then used along with a likelihood function that describes the relationship between poses and images captured in the video. Through Bayesian inference, the most likely pose at each frame is computed.

Evaluation: The system is evaluated in four different experiments. The first three experiments use monocular video data of different nontrivial locomotion scenarios: variable speed walking, occlusion (walking behind obstacles), and turning out of the camera plane. The fourth experiment involves testing on a pre-existing benchmark dataset. The fourth experiment allows for explicit quantitative analysis of the accuracy of the results.

Reproducible: I believe this paper would be very difficult to reproduce. Many details of the implementation are left out or incomplete, such as the methods used to extract data from the video frames. It shouldn't be impossible, however, since most of the gaps can likely be filled in with other papers and tools from related fields like computer vision, inverse kinematics and Bayesian inference. By itself, though, I don't think this paper provides sufficient detail to reproduce its results.

Improvement: 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

-- MichielVanDePanne - 27 Nov 2011