Abstract
This paper presents a low-cost real-time alternative to available commercial human motion capture systems. First, a set of distinguishable markers are placed on several human body landmarks, and the scene is captured by a number of calibrated and synchronized cameras. In order to establish a physical relation among markers, a human body model is defined. Markers are detected on all camera views and delivered as the input of an annealed particle filter scheme where every particle encodes an instance of the pose of the body model to be estimated. Likelihood between particles and input data is performed through the robust generalized symmetric epipolar distance and kinematic constrains are enforced in the propagation step towards avoiding impossible poses. Tests over the HumanEva annotated data set yield quantitative results showing the effectiveness of the proposed algorithm. Results over sequences involving fast and complex motions are also presented.
Highlights
Accurate retrieval of the configuration of an articulated structure from the information provided by multiple cameras is a field that found numerous applications in the recent years
This paper focuses on human motion capture (HMC) systems with passive markers in a multicamera scenario
Addressing a complex problem such as human motion capture using EM is perhaps manageable in a benevolent scenario with well learnt constrains but, as suggested by Caillete and Howard [36] in the comparison of EM- and Particle Filtering (PF)- based methods, Monte Carlo-based techniques clearly outperform those based in minimization algorithms
Summary
Accurate retrieval of the configuration of an articulated structure from the information provided by multiple cameras is a field that found numerous applications in the recent years. Medicine benefited from these advances in the field of orthopedics, locomotive pathologies assessment, or sports performance improvement [2]. In this field, despite markerless HMC systems have attained significant performance ratios in some scenarios [3], only HMC systems aided by markers placed on some body landmarks can produce high-accuracy results. Optical systems based on photogrammetric methods are more used than the nonoptical ones, usually requiring special suits embedding rigid skeletal-like structures [4], magnetic [5] or accelerometric devices [6] or multisensor fusion algorithms [7]. Image-based or optical systems allow a relative freedom of movement and are less intrusive
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