
1. Title: Vicon Physical Action DataSet


2. Sources:
   - Original owner: Theo Theodoridis
     School of Computer Science and Electronic Engineering
     University of Essex
     Wivenhoe Park, Colchester, CO4 3SQ, UK
     ttheod@gmail.com
     http://sites.google.com/site/ttheod/
   - Donors: Theo Theodoridis
   - Date: 28/07/11


3. Past Usage:
   - T. Theodoridis and H. Hu, Classifying Aggressive Actions of 3D Human Models Using
     Dynamic ANNs for Mobile Robot Surveillance, IEEE International Conference on Robotics
     and Biomimetics (Robio-2007), Dec. 15-18, 2007, pp. 371-376.

   - T. Theodoridis, A. Agapitos, H. Hu, and S. M. Lucas, Ubiquitous Robotics in Physical
     Human Action Recognition: A Comparison Between Dynamic ANNs and GP, IEEE International
     Conference on Robotics and Automation (ICRA-2008), May 19-23, 2008, pp. 3064-3069.

   - T. Theodoridis and H. Hu, A Fuzzy-Convolution Model for Physical Action and Behaviour
     Pattern Recognition of 3D Time Series, IEEE Int. Conference on Robotics and Biomimetics
     (Robio-2008), Feb. 21-26, 2009, pp. 407-412.

   - T. Theodoridis, A. Agapitos, H. Hu, and S. M. Lucas, Mechanical Feature Attributes for
     Modeling and Pattern Classification of Physical Activities, IEEE International Conference
     in Information and Automation (ICIA-2009), June 22-24, 2009, pp. 528-533.

   - T. Theodoridis, A. Agapitos, H. Hu, and S. M. Lucas, A QA-TSK Fuzzy Model versus Evolutionary
     Decision Trees Towards Nonlinear Action Pattern Recognition, IEEE International Conference in
     Information and Automation (ICIA-2010), June 20-23, 2010, pp. 1813-1818.

   - T. Theodoridis, P. Theodorakopoulos, and H. Hu, Evolving Aggressive Biomechanical Models with
     Genetic Programming, IEEE/RSJ International Conference on Intelligent Robots and Systems,
     (IROS-2010), Oct. 18-22, 2010, pp. 2495-2500.

   - T. Theodoridis, A. Agapitos, and H. Hu, A Gaussian Groundplan Projection Area Model for
     Evolving Probabilistic Classifiers, GECCO Genetic and Evolutionary Computation Conference
     (GECCO-2011), Jul. 12-16, 2011, pp. 1339-1346.


4. Relevant Information:
   4.1 Protocol:
       Seven male and three female subjects (age 25 to 30), who have experienced aggression in scenarios such
       as physical fighting, took part in the experiment. Throughout 20 individual experiments, each subject
       had to perform ten normal and ten aggressive activities. Regarding the rights of the subjects involved,
       ethical regulations have been followed based on the code of ethics of the British psychological society,
       which explains the ethical legislations to conduct statistical experiments using human subjects. For safety
       precaution issues, boxing hand wraps have been given to the subjects, and for the warm up the subjects
       were instructed to familiarise with the bag by having a number of trial runs. The subjects were aware that
       since their involvement in this series of experiments was voluntary, it was made clear that they could
       withdraw at any time from the study.

   4.2 Instrumentation:
       The Essex robotic arena was the main experimental hall where the data collection took place. With area
       4x5.5m, the ten subjects expressed normal and aggressive physical activities at random locations. For the
       normal actions, a human partner has been used as a focus target attracting the attention from the subjects
       so as to perform more realistic activity. For the aggressive actions, the subjects made use of a professional
       kick-boxing standing bag, 1.75m tall, with a human figure drawn on its body. The bag has cylindrical shape
       made from soft material, which could bounce when hit. All the activities have been recorded from random
       starting positions so that to have a variety of spatial 3D data. The subjects’ performance has been recorded
       by the Vicon’s nine ubiquitous cameras, interfacing human activity with spatial coordinate points. Based on
       this context, the data acquisition process involved four reflectable markers placed on the forearms (elbows
       and wrists), four on the forelegs (knees and ankles), and one on the top of the head.

   4.3 Data Setup:
       Each experimental trial has been taken separately for each physical activity. The duration of each action
       was approximately ~10 seconds per subject, which corresponds to a time series of ~3000 samples, with
       sampling frequency of 200Hz. Within this performance time, approximately 15 action trajectories were
       extracted counting in average 15 normal (ex: handshaking), and 15 aggressive (ex: punching) actions.


5. Number of Instances: ~3,000 


6. Number of Attributes: 27


7. Attribute Information:
   Each file in the dataset contains in overall 28 columns (the 1st is a counter), and is organised as follows:

   +---------+-------+---------------+---------------------+---------------------+---------------------+
   | Segment | Head  |     L-Arm     |        R-Arm        |        L-Leg        |        R-Leg        |
   +---------+-------+-------+-------+----------+----------+----------+----------+----------+----------+
   | Marker  | m1    | m2    | m3    | m4       | m5       | m6       | m7       | m8       | m9       |
   | Coords  | x y z | x y z | x y z | x  y  z  | x  y  z  | x  y  z  | x  y  z  | x  y  z  | x  y  z  |
   | Column  | 1,2,3 | 4,5,6 | 7,8,9 | 10,11,12 | 13,14,15 | 16,17,18 | 19,20,21 | 22,23,24 | 25,26,27 |
   +---------+-------+-------+-------+----------+----------+----------+----------+----------+----------+

   Segment: A segment defines a body segment or limb.
	    - Head
	    - Left arm (L-Arm)
	    - Right arm (R-Arm)
	    - Left leg (L-Leg)
	    - Right leg (R-Leg)

   Marker:  A pair of markers (except the head) is attached at each body segment for 3D data acquisition.
	    - Arm markers: wrist (WRS), elbow (ELB)
	    - Leg markers: ankle (ANK), knee (KNE)

   Coords:  The 3 coordinates (x,y,z) define the 3D position of each marker in space.
	    - x: The x coordinate
	    - y: The y coordinate
	    - z: The z coordinate


8. Number of Classes: 20
   The dataset consists of 10 normal, and 10 aggressive physical actions.
   Normal: Bowing, Clapping, Handshaking, Hugging, Jumping, Running, Seating, Standing, Walking, Waving
   Aggressive: Elbowing, Frontkicking, Hamering, Headering, Kneeing, Pulling, Punching, Pushing, Sidekicking, Slapping
