Real-Time Gesture Recognition with a 2D camera

Real-Time Gesture Recognition with a 2D camera

Yadhunathan, S.

Kuzmanov, G. (mentor)

Electrical Engineering, Mathematics and Computer Science

Microelectronics & Computer Engineering

Embedded Systems

2011-08-30

There has been a vast improvement in Human-Computer Interaction over the last decade. Yet there are only a very few systems with natural interfaces such as with speech and gestures. This thesis here addresses the topic of gesture recognition using a 2D camera and how they can be used as natural interfaces to control applications. The gesture recognition algorithm can identify six different gestures and was first developed in a PC and later moved to an embedded platform. A robust background subtraction technique is designed to obtain the hand segment. Two gesture recognition methods are implemented, their performances are measured and the angle-based recognition approach is chosen for its accuracy. The application is moved to an embedded platform i.MX515EVK based on ARM Cortex-A8 processor. To obtain a frame rate suitable for real-time applications, optimizations such as camera capture time reduction, algorithmic optimizations and utilizing SIMD unit of the Cortex-A8 processor known as NEON for data parallelism are performed. As experimentation, the optimized version of the algorithm is used to build a real-time application that recognizes gesture from images to control applications. The performance of the application is studied and a frame rate of 4 - 4.5 frames per second is achieved.

Gesture Recognition
iMX515

http://resolver.tudelft.nl/uuid:004841ea-8251-42e2-ab76-b3034dcf03ce

2015-09-11

Student theses

master thesis

(c) 2011 Yadhunathan, S.