My research

Visions of smart houses and home automation technologies have been around for over three decades. Since that time, computers and technology have made a huge step forward and simple home automation is not so appealing anymore. In this paper we propose and prototype an intelligent living room system that without intended interaction enhances people everyday life by figuring out our desires from our natural gestures, facial expressions and speech. In order to achieve this, artificial intelligence and machine learning algorithms, such as Support Vector Machine (SVM) and Hidden Markov Model (HMM) are used. Microsoft Kinect for Windows sensor is used to monitor gestures, voice and locate people in the living room. High definition camera is used in detecting facial expressions. The information gathered from multiple sensors and users’ desires recognized from gestures and facial expressions are combined in order to make correct decisions. As a result, the system seamlessly enhances people everyday life by making it more comfortable. The system will learn each individual’s preferences in different situations. It will adapt to different users and take actions based on user’s postures, gestures, speech and facial expressions and also location in the room. The system will make every day life much more comfortable.

Pictures

Kinect for Windows
[ Kinect for Windows ]
Depth + skeleton tracking
[ Depth + skeleton tracking ]

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