This paper reports a combined depth- and model-based face detection and tracking approach. The proposed algorithm consists of four functional modules; i) color-based candidate region extraction, ii) generation of the depth histogram for handling occlusion, iii) rotation-invariant face region detection using ellipse fitting, and iv) face tracking based on motion prediction. This technique solved the occlusion problem under complicated environment by detecting the face candidate region based on the depth-based histogram and skin colors. The angle of rotation was estimated by the ellipse fitting method in the detected candidate regions. The face region was finally determined by inversely rotating the candidate regions by the estimated angle using Haar-like features that were robustly trained robustly by the frontal face.

In this paper, we address the tracking problem caused by camera motion and rolling shutter effects associated with CMOS sensors in consumer handheld cameras, such as mobile cameras, digital cameras, and digital camcorders. A modified particle filtering method is proposed for simultaneously tracking objects and compensating for the effects of camera motion. The proposed method uses an elastic registration algorithm (ER) that considers the global affine motion as well as the brightness and contrast between images, assuming that camera motion results in an affine transform of the image between two successive frames. By assuming that the camera motion is modeled globally by an affine transform, only the global affine model instead of the local model was considered. Only the brightness parameter was used in intensity variation. The contrast parameters used in the original ER algorithm were ignored because the change in illumination is small enough between temporally adjacent frames. The proposed particle filtering consists of the following four steps: (i) prediction step, (ii) compensating prediction state error based on camera motion estimation, (iii) update step and (iv) re-sampling step. A larger number of particles are needed when camera motion generates a prediction state error of an object at the prediction step. The proposed method robustly tracks the object of interest by compensating for the prediction state error using the affine motion model estimated from ER. Experimental results show that the proposed method outperforms the conventional particle filter, and can track moving objects robustly in consumer handheld imaging devices.

Many hand gesture recognition systems using advanced computer vision techniques to eliminate the need for a TV remote controller have been proposed. Nevertheless, some issues still remain, such as high computational complexity and insufficient information on the target object and background. Moreover, none of the proposed techniques consider how to enter the control mode of the system. This means that they may need a TV remote controller to enter the control mode. This paper proposes a hand mouse system using a pre-defined gesture with high background adaptability. By doing so, a remote controller to enter the control mode of the IPTV system can be eliminated.

The widespread implementation of RFID in ubiquitous computing is constrained considerably by privacy and security unreliability of the wireless communication channel. This failure to satisfy the basic, security needs of the technology has a direct impact of the limited computational capability of the tags, which are essential for the implementation of RFID. Because the universal application of RFID means the use of low cost tags, their security is limited to lightweight cryptographic primitives. Therefore, EPCGen2, which is a class of low cost tags, has the enabling properties to support their communication protocols. This means that satisfying the security needs of EPCGen2 could ensure low cost security because EPCGen2 is a class of low cost, passive tags. In that way, a solution to the hindrance of low cost tags lies in the security of EPCGen2. To this effect, many lightweight authentication protocols have been proposed to improve the privacy and security of communication protocols suitable for low cost tags. Although many EPCgen2 compliant protocols have been proposed to ensure the security of low cost tags, the optimum security has not been guaranteed because many protocols are prone to well-known attacks or fall short of acceptable computational load. This paper proposes a remedy protocol to the flyweight RFID authentication protocol proposed by Burmester and Munilla against a desynchronization attack. Based on shared pseudorandom number generator, this protocol provides mutual authentication, anonymity, session unlinkability and forward security in addition to security against a desynchronization attack. The desirable features of this protocol are efficiency and security.

The huge success of location-aware applications has called for the rapid development of an alternative positioning system to the global positioning system (GPS) for indoor localization based on existing technologies, such as 802.11 wireless networks. This paper proposes the Wireless MAC Processor Positioning System (WMPS), which is a localization system running on off-the-shelf 802.11 Access Points and based on the time-of-flight ranging of users' standard terminals. This paper proves through extensive experiments that the propagation delays can be measured with the accuracy required by indoor applications despite the different noise components that can affect the result: latencies of the hardware transreceivers, multipath, ACK jitters and timer quantization. Key to this solution is the choice of the Wireless MAC Processor architecture, which enables a straightforward implementation of the ranging subsystem directly inside the commercial cards without affecting the basic DCF channel access algorithm. In addition to the proposed measurement framework, this study developed a simple and effective localization algorithm that can work without requiring any preliminary calibration or device characterization. Finally, the architecture allows the measurement methodology to be adjusted as a function of the network load or propagation environments at the run time, without requiring any firmware update.

A client collaboration (CC) system is proposed for a user relay system. The proposed scheme focuses on the management of transmit power and leakage interference. In the proposed CC system, edge users transmit signals to the masters considered as user relays. The masters relay the signals of the edge users to the base station using the resource blocks (RBs) that are assigned to the edge users. The leakage interference and power consumption were analyzed in the CC system. In addition, an optimal master location problem was formulated based on the signal-to-leakage-plus-noise ratio (SLNR). Because the optimal master location problem is quite complex, a sub-optimal master location problem was proposed and a closed-form sub-optimal master location was obtained. The edge users generate smaller leakage interference and power consumption in the proposed CC system compared to the system without the CC. The numerical results showed that the edge users generate smaller leakage interference and power consumption in the proposed CC system compared to the system without the CC, and the average throughput increases.