Introduction of Motion Analysis

November 23, 2017 Author: rajesh
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The ultimate goal of computer vision is to understand the scene correctly through various steps of acquiring, processing, analyzing and understanding different kinds of information obtained by different kinds of sensors. Human motion analysis, recognition, and understanding are one of the very hottest topics within computer vision.

Aspect of Motion Analysis

As one of the most active research areas in computer vision, visual analysis of human motion attempts to detect, track and identify people, and more generally, to interpret human behaviors, from image sequences involving humans. Human motion analysis has attracted great interests from computer vision researchers due to its promising applications in many areas such as visual surveillance, perceptual user interface, content-based image storage and retrieval, video conferencing, athletic performance analysis, virtual reality, etc. Vision based human motion recognition is a systematic approach to understand and analyze the movement of people in camera captured content. It comprises of fields such as Biomechanics, Machine Vision, Image Processing, Artificial Intelligence and Pattern Recognition. It is an interdisciplinary challenging field having grand applications with social, commercial, and educational benefits. A wide spectrum of applications demands human motion recognition. Human motion analysis is a broad concept.

Directions of human motion analysis explored

Figure 1: Directions of human motion analysis explored: gesture recognition, hand pose estimation and user validation from motion

Application Area

Human motion analysis has been explored in parallel by different research communities and from different perspectives. Today, it has evolved into collection of isolated standard tasks, ranging from interpreting subtle facial expressions to crowd motion analysis. Visual analysis of human motion has recently persuaded more studies in the computer vision area. It attempts to detect, track, and identify people, and more generally, to understand human behaviors from image sequences involving humans. Different applications are categorized according to current trends.

Potential Applications

Human motion analysis has a wide range of potential applications such as smart surveillance, advanced user interface, motion based diagnosis, to name a few.

  • Video Surveillance: The strong need of smart surveillance systems stems from those security-sensitive areas such as banks, department stores, parking lots, and borders. Surveillance cameras are already prevalent in commercial establishments, while camera outputs are usually recorded in tapes or stored in video archives. These video data is currently used only “after the fact” as a forensic tool, losing its primary benefit as an active real-time media. What is needed is the real-time analysis of surveillance data to alert security officers to a burglary in progress, or to a suspicious individual wandering around in the parking lot.
  • Advanced user interface: Another important application domain is advanced user interfaces in which human motion analysis is usually used to provide control and command. Generally speaking, communication among people is mainly realized by speech. Therefore, speech understanding has already been widely used in early human-machine interfaces. However, it is subject to the restrictions from environmental noise and distance. Vision is very useful to complement speech recognition and natural language understanding for more natural and intelligent communication between human and machines.
  • Motion based Diagnosis and Identification: It is particularly useful to segment various body parts of human in an image, track the movement of joints over an image sequence, and recover the underlying 3-D body structure for the analysis and training of athletic performance. With the development of digital libraries, interpreting video sequences automatically using content-based indexing will save tremendous human efforts in sorting and retrieving images or video in a huge database.


[1] Natalia Neverova “Deep learning for human motion analysis”, PhD dissertation, INSA Lyon, 2016

[2] Liang Wang, Weiming Hu and Tieniu Tan “Recent developments in human motion analysis”, Pattern recognition 36, no. 3 (2003): pp. 585-601.

[3] Thomas B. Moeslund, Adrian Hilton, and Volker Krüger, “A survey of advances in vision-based human motion capture and analysis”, Computer vision and image understanding 104, no. 2 (2006): 90-126.

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