Difference: PhysicsTracking (3 vs. 4)

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