Hand gesture recognition has been applied to many fields in recent years, especially in man-machine interaction (MMI) area, which is regarded as a more natural and flexible input than the traditional input, such as, mice and keyboard. Microsoft Kinect camera has also drastically changed the world of human computer interaction based computer vision, due to its low cost and high quality of depth information for visual images. This has made the depth data to become common place at a very low cost allowing myriad of computer vision related applications including hand gesture recognition. Hand gesture recognition research suffered severely from the clutter and skintone regions in any background. With the availability of depth information, background clutter and skintone regions which are not part of the hand gesture can be removed improving the performance of any classification strategy. In this thesis, an overview of hand gesture recognition research up to date is presented, which includes common stages of hand gesture recognition, common methods and technique of each stage, the state of the recent research and summaries of some successful hand gesture recognition models. This article also discusses a novel hand detection strategy based on Kinect camera by combining depth and colour image information. In the detection procedure, the Kalman filter is applied to tracking process to achieve a good detection result. The experiment results in chapter 3 show this detection method is reliable and

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Robust human computer interaction using dynamic hand gesture recognition

Bright spots are usually seen in seismic sections that can be interpreted as gas reservoirs. These local anomalies are identified as an increase in amplitudes on a seismic section. However, bright spots are not always gas indicators. They are also produced because of lithology changes. In this case, to prevent great costs of drilling, we need to understand the cause of bright spots. In this paper we use two methods which are mainly based on frequency and velocity analysis of seismic waves. Therefore, we apply simultaneous seismic inversion and S-transform on a 2D pre-stack seismic data which in its CDP gathers, several bright spots are seen. We just choose two of these bright spots arbitrarily. If they are due to hydrocarbon, P-wave velocity decreases sharply while S-wave velocity increases slightly, therefore decreases. Similarly, high frequencies being eliminated in the hydrocarbon areas. In contrast, if the bright spot is produced due to lithology change (gas saturated limestone/ limestone interface) then frequency and P-wave velocity will increase while S-velocity decreases.

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Application of S-Transform and Simultaneous Seismic Inversion to Interpret Bright Spots

For realization the controller of robot automatically recognize the peripherals, add or remove, and auto-complete device initialization and peripheral equipment acquisition to intelligent design of the information displayed in human-computer interaction interface proposed to use the Cortex-M3 and Cortex-A8 dual ARM core system architecture. Use the Cortex-M3 core STM32F103VCT6 processor to monitoring of peripheral devices added or removed to complete the sensor data acquisition; use Cortex-A8 core OMAP3530 embedded processor, embedded Linux operating system as relying on QT / Embedded GUI development environment, human-computer interaction interface structures using the method of cross-compile to complete the development of the ARM-side man-machine interface. Through the serial communication STM32F103VCT6 processor OMAP3530 embedded processor data transfer, completion of the collected sensor information to the human-computer interaction interface. Able to complete the automatic identification verified by experiments the robot intelligent controller and initialize peripherals, collected information to the interactive interface.

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The robot intelligent controller design and implementation base on ARM

The EHA (electro hydraulic actuator) has a notable advantage over conventional hydraulic actuators as it uses a closed-loop circuit, reducing the size and volume of oil, and eliminates pressure losses caused by valve orifices. However, accurate control performance of EHA is difficult to achieve using a traditional PID (proportional integral derivative) controller due to the strongly nonlinear, time-varying, and unknown dynamics of the system. Hence this paper seeks to address this problem by proposing a design of an intelligent controller for the EHA. The proposed adaptive fuzzy sliding mode controller (AFSMC) is developed as a hybrid of the adaptive, fuzzy logic, and sliding mode algorithms. To reduce costs and time, a virtual prototype approach is also proposed instead of experimentations to evaluate the performance of the proposed controller. The virtual model of the EHA is built in Amesime software, and then embedded into Matlab/Simulink where the AFSMC is developed and tested to obtain the position responses of the EHA. The results show that the AFSMC is highly successful and more efficient than the traditional PID at controlling the position of the piston accurately.

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Development of an Adaptive Fuzzy Sliding Mode Controller of an Electrohydraulic Actuator Based on a Virtual Prototyping

These two volumes constitute the refereed proceedings of the First International Conference on Intelligent Robotics and Applications, ICIRA 2008, held in Wuhan, China, in October 2008. The 265 revised full papers presented were thoroughly reviewed and selected from 552 submissions; they are devoted but not limited to robot motion planning and manipulation; robot control; cognitive robotics; rehabilitation robotics; health care and artificial limb; robot learning; robot vision; human-machine interaction & coordination; mobile robotics; micro/nano mechanical systems; manufacturing automation; multi-axis surface machining; real world applications.

C. Xiong

Papers

Intelligent Robotics and Applications: First International Conference, ICIRA 2008 Wuhan, China, October 15-17, 2008 Proceedings, Part II