Shane Kinsella th year Electronic Engineering 4BN1 NUI Galway Supervisor: Peter Corcoran March 2009

Concept To investigate facial detection with reference to OpenCV and the Viola Jones technique Explore parameters which effect the detection time Optimise facial detection using knowledge about video streams and the movement of objects

Applications Any detection system that is required to run in real- time or at very high frame rates System does not have to detect faces, this system may be extended to work while detecting any object (given detect rules for that object) Knowledge of the movement patterns of that object needs to be either known or learned on the fly This system may be combined with other optimisation techniques to form a basis for real- time object tracking used in AI

Work Carried Out Researched OpenCV (API) and Python (programming language) Researched the Viola and Jones method of facial detection Found example code of facial detection using OpenCV Tested the detection time of facial detection when varying the parameters involved Investigated movement patterns of faces on a webcam Used this knowledge to define limits for optimised code

Optimisations which were applied Scan area limited to a region around a previously detected face Minimum face size is limited to a value which is proportional to the size of the previously detected face

Issues Encountered Project Specific Coding issues Introduction of new faces Elimination of duplicate faces The velocity question Setup of Python and OpenCV Applying facial detection to sub regions of an image Keyboard handling Visibility of variables Memory usage runaway

Reason for Discarding Velocity A high frame rate is essential to the operation of a system which uses the previous position and the previous velocity This is so that the system may pick up changes in velocity ex. A moving object suddenly stops A higher frame rate means that objects will travel less from one frame to another As the distance travelled by an object gets less and less, any advantage gained by introducing velocity also gets reduced

Reason for Discarding Velocity (Summary) High frame rate is essential to proper operation Becomes less effective (ineffective) the higher the frame rate

Results Frame rates have been noted to improve by a factor of 5+ (typical 4 FPS to 20+ FPS) Adapting the minimum face size accounts for the greatest improvement FPS improvement without adaptable min face size approx 2 times faster

Features of Solution Code Polled based keyboard input Refreshes new faces when: Spacebar pressed No faces were found previously Many display features for displaying data Can vary the tracking parameters used Can swap between un-optimised detection and optimised detection (key 6) Can toggle the use of adaptable minimum face size (for comparison purposes)

Display Options Key 1: toggle display faces detected (on by default) Key 2: toggle display scan area used per face Key 3: toggle display min face size used per face Key 4: toggle print FPS to the console window

Configuration Options Key 5: toggle un-optimised/optimised detection Key 6: toggle use of adaptable min face size Key w or s: select the variable you wish to vary (2 supported) Scan area size Minimum face size Key a or d: vary the selected variable Key 0: restore all of the default settings