Motion analysis

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Researchers, engineers, and technicians have come to rely on video cameras as non-invasive testing devices. In industrial, scientific, clinical, and academic environments, video cameras provide a method of evaluating motion and performance from a distance, without interference from sensors. Motion analysis software can provide time-dependent, quantitative data on any movement captured using digital video.

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[edit] Human Motion Analysis

In the areas of medicine, sports, and video surveillance, human motion analysis has become an investigative and diagnostic tool. See the section on motion capture for more detail on the technologies. Human motion analysis can be divided into three categories: human activity recognition, human motion tracking, and analysis of body and body part movement.

Human activity recognition is most commonly used for video surveillance, specifically automatic motion monitoring for security purposes. Most efforts in this area rely on state-space approaches, in which sequences of static postures are statistically analyzed and compared to modeled movements. Template-matching is an alternative method whereby static shape patterns are compared to pre-existing prototypes.[1]

Human motion tracking can be performed in two or three dimensions. Depending on the complexity of analysis, representations of the human body range from basic stick figures to volumetric models. Tracking relies on the correspondence of image features between consecutive frames of video, taking into consideration information such as position, color, shape, and texture. Edge detection can be performed by comparing the color and/or contrast of adjacent pixels, looking specifically for discontinuities or rapid changes.[2] Three-dimensional tracking is fundamentally identical to two-dimensional tracking, with the added factor of spatial calibration.[1]

Motion analysis of body parts is critical in the medical field. In postural and gait analysis, joint angles are used to track the location and orientation of body parts. Gait analysis is also used in sports to optimize athletic performance or to identify motions that may cause injury or strain. Tracking software, such as Xcitex ProAnalyst or Photron Motion Tools, that does not require the use of optical markers is especially important in these fields, where the use of markers may impede natural movement.[3][1]

[edit] Motion Analysis in Manufacturing

Motion analysis is also applicable in the manufacturing process. Using high speed video cameras and motion analysis software, one can monitor and analyze assembly lines and production machines to detect inefficiencies or malfunctions. Manufacturers of sports equipment, such as baseball bats and hockey sticks, also use high speed video analysis to study the impact of projectiles. An experimental setup for this type of study typically uses a triggering device, external sensors (e.g., accelerometers, strain gauges), data acquisition modules, a high-speed camera, and a computer for storing the synchronized video and data. Motion analysis software calculates parameters such as distance, velocity, acceleration, and deformation angles as functions of time. This data is then used to design equipment for optimal performance.[4]

[edit] Additional Applications for Motion Analysis

The object and feature detecting capabilities of motion analysis software can be applied to count and track particles, such as bacteria, viruses[5] Motion analysis is also used widely in the military for ballistics testing, analyzing high-speed phenomena like hydrodynamic ram. “Flight-following” motion analysis software, such as ProAnalyst 3-D Flight Path Edition, is especially useful in studying projectile motion and can be utilized to extract trajectory time history behavior from high-speed digital video.[6]

[edit] References

  1. ^ a b c Aggarwal, JK and Q Cai. "Human Motion Analysis: A Review." Computer Vision and Image Understanding 73, no. 3 (1999): 428-440.
  2. ^ Fan, J, EA El-Kwae, M-S Hacid, and F Liang. "Novel tracking-based moving object extraction algorithm." J Electron Imaging 11, 393 (2002).
  3. ^ Green, RD, L Guan, and JA Burne. "Video analysis of gait for diagnosing movement disorders." J Electron Imaging 9, 16 (2000).
  4. ^ Masi, CG. "Vision improves bat performance." Vision Systems Design. June 2006
  5. ^ Shopov, A. et al. "Improvements in image analysis and fluorescence microscopy to discriminate and enumerate bacteria and viruses in aquatic samples, or cells, and to analyze sprays and fragmenting debris." Aquatic Microbial Ecology 22 (2000): 103-110.
  6. ^ Sparks, C. et al. "Comparison and Validation of Smooth Particle Hydrodynamics (SPH) and Coupled Euler Lagrange (CEL) Techniques for Modeling Hydrodynamic Ram." 46th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, Austin, Texas, Apr. 18-21, 2005.