Master's thesis at the University of Basrah discussing (following people in a smart room)
a master's thesis at the College of Engineering at the University of Basrah discussing (Tracking people in a smart room). It dealt with the thesis presented by the student Heba Adel Salem
Suggesting a way to track people in a smart room using a Kinect sensor
For data classification, three methods, SVM, RF, ANN were used to achieve this goal. 14 types of movements were identified. Experiments were conducted on 12 people who perform all movements in each experiment. Training DataSet was created manually by capturing people’s movements during all experiments. The system was tested on Adults to classify their actions, their movements were recorded and experiments were conducted on 4 adults, each person performing 14 movements Repeat each one four times, with an interval of 10 to 20 seconds for each movement
The thesis aims to track people in a smart room
The thesis obtained from the SVM model test shows that the average accuracy is 81.2%, 92.3% from the random forest model test, and 51.53% from the ANN test.
