The conical area evolutionary algorithm (CAEA) has a very high run-time efficiency for bi-objective optimization, but it can not tackle problems with more than two objectives. In this letter, a conical hypervolume evolutionary algorithm (CHEA) is proposed to extend the CAEA to a higher dimensional objective space. CHEA partitions objective spaces into a series of conical subregions and retains only one elitist individual for every subregion within a compact elitist archive. Additionally, each offspring needs to be compared only with the elitist individual in the same subregion in terms of the local hypervolume scalar indicator. Experimental results on 5-objective test problems have revealed that CHEA can obtain the satisfactory overall performance on both run-time efficiency and solution quality.

Many previous studies on image quality assessment of 3D still images or video clips have been conducted. In particular, it is important to know the region in which assessors are interested or on which they focus in images or video clips, as represented by the ROI (Region of Interest). For multi-view 3D images, it is obvious that there are a number of viewpoints; however, it is not clear whether assessors focus on objects or background regions. It is also not clear on what assessors focus depending on whether the background region is colored or gray scale. Furthermore, while case studies on coded degradation in 2D or binocular stereoscopic videos have been conducted, no such case studies on multi-view 3D videos exist, and therefore, no results are available for coded degradation according to the object or background region in multi-view 3D images. In addition, in the case where the background region is gray scale or not, it was not revealed that there were affection for gaze point environment of assessors and subjective image quality. In this study, we conducted experiments on the subjective evaluation of the assessor in the case of coded degradation by JPEG coding of the background or object or both in 3D CG images using an eight viewpoint parallax barrier method. Then, we analyzed the results statistically and classified the evaluation scores using an SVM.

A regional protection system based on a wireless Ad-Hoc network has been in operation since 2008 in Shiojiri City, Japan. Wireless terminals transmit data packets to a server via transponders situated around the city. In this paper, a new routing algorithm that takes into account the level of congestion of the transponders is proposed. Using computer simulations, the proposed algorithm is shown to reduce the packet loss rate compared to the previous algorithm which is based on minimization of the number of hops to the server. Also, the proposed algorithm is shown be have almost the same packet loss rate as the best routing decisions obtained by an exhaustive search. Furthermore, the simulations used recreate the actual movement of terminals, so the results show what will happen in a realistic environment.

Information-theoretic limits of a multi-way relay channel with direct links (MWRC-DL), where multiple users exchange their messages through a relay terminal and direct links, are discussed in this paper. Under the assumption that a restricted encoder is employed at each user, an outer bound on the capacity region is derived first. Then, a decode-and-forward (DF) strategy is proposed and the corresponding rate region is characterized. The explicit outer bound and the achievable rate region for the Gaussian MWRC-DL are also derived. Numerical examples are provided to demonstrate the performance of the proposed DF strategy.

A new exemplar-based inpainting method which effectively preserves global structures and textures in the restored region driven by feature vectors is presented. Exemplars that belong to the source region are segmented based on their features. To express characteristics of exemplars such as shapes of structures and smoothness of textures, the Harris corner response and the variance of pixel values are employed as a feature vector. Enhancements on restoration plausibility and processing speedup are achieved as shown in the experiments.

This paper proposes a novel method for determining a three-dimensional (3D) bounding box to estimate pose (position and orientation) and size of a 3D object corresponding to a segmented object region in an image acquired by a single calibrated camera. The method is designed to work upon an object on the ground and to determine a bounding box aligned to the direction of the object, thereby reducing the number of degrees of freedom in localizing the bounding box to 5 from 9. Observations associated with the structural properties of back-projected object regions on the ground are suggested, which are useful for determining the object points expected to be on the ground. A suitable base is then estimated from the expected on-ground object points by applying to them an assumption of bilateral symmetry. A bounding box with this base is finally constructed by determining its height, such that back-projection of the constructed box onto the ground minimally encloses back-projection of the given object region. Through experiments with some 3D-modelled objects and real objects, we found that a bounding box aligned to the dominant direction estimated from edges with common direction looks natural, and the accuracy of the pose and size is enough for localizing actual on-ground objects in an industrial working space. The proposed method is expected to be used effectively in the fields of smart surveillance and autonomous navigation.

The increasing demand of indoor location based service (LBS) has promoted the development of localization techniques. As an important alternative, fingerprinting localization technique can achieve higher localization accuracy than traditional trilateration and triangulation algorithms. However, it is computational expensive to construct the fingerprint database in the offline phase, which limits its applications. In this paper, we propose an efficient indoor positioning system that uses a new empirical propagation model, called regional propagation model (RPM), which is based on the cluster based propagation model theory. The system first collects the sparse fingerprints at some certain reference points (RPs) in the whole testing scenario. Then affinity propagation clustering algorithm operates on the sparse fingerprints to automatically divide the whole scenario into several clusters or sub-regions. The parameters of RPM are obtained in the next step and are further used to recover the entire fingerprint database. Finally, the location estimation is obtained through the weighted k-nearest neighbor algorithm (WkNN) in the online localization phase. We also theoretically analyze the localization accuracy of the proposed algorithm. The numerical results demonstrate that the proposed propagation model can predict the received signal strength (RSS) values more accurately than other models. Furthermore, experiments also show that the proposed positioning system achieves higher localization accuracy than other existing systems while cutting workload of fingerprint calibration by more than 50% in the offline phase.

With the advances in wireless Internet and mobile positioning technology, location-based services (LBSs) have become popular. In LBSs, users must send their exact locations in order to use the services, but they may be subject to several privacy threats. To solve this problem, query processing algorithms based on a cloaking method have been proposed. The algorithms use spatial cloaking methods to blur the user's exact location in a region satisfying the required privacy threshold (k). With the cloaked region, an LBS server can execute a spatial query processing algorithm preserving their privacy. However, the existing algorithms cannot provide good query processing performance. To resolve this problem, we, in this paper, propose a k-NN query processing algorithm based on network Voronoi diagram for spatial networks. Therefore, our algorithm can reduce network expansion overhead and share the information of the expanded road network. In order to demonstrate the efficiency of our algorithms, we have conducted extensive performance evaluations. The results show that our algorithm achieves better performance on retrieval time than the existing algorithms, such as PSNN and kRNN. This is because our k-NN query processing algorithm can greatly reduce a network expansion cost for retrieving k POIs.

Dynamic spectrum access is the key approach in cognitive wireless regional area networks, and it is adopted by secondary users to access the licensed radio spectrum opportunistically. In order to realize real-time secondary spectrum usage, a dynamic spectrum access model based on stochastic differential games is proposed to realize dynamic spectrum allocation; a Nash equilibrium solution to the model is given and analyzed in this paper. From an overall perspective, the relationships between available spectrum percentage and the spectrum access rate are studied. Changes in the available spectrum percentage of the cognitive wireless regional area networks involve a deterministic component and a stochastic component which depends upon an r-dimensional Wiener process. The Wiener process represents an accumulation of random influences over the interval, and it reflects stochastic and time-varying properties of the available spectrum percentage. Simulation results show that the dynamic spectrum access model is efficient, and it reflects the time-varying radio frequency environment. Differential games are useful tools for the spectrum access and management in the time-varying radio environment.

A new artificial fish swarm algorithm (AFSA) for solving the multiple knapsack problem (MKP) is introduced in this paper. In the proposed AFSA, artificial fish (AF) individuals are only allowed to search the region near constraint boundaries of the problem to be solved. For this purpose, several behaviors to be performed by AF individuals, including escaping behavior, randomly moving behavior, preying behavior and following behavior, were specially designed. Exhaustive experiments were implemented in order to investigate the proposed AFSA's performance. The results demonstrated the proposed AFSA has the ability of finding high-quality solutions with very fast speed, as compared with some other versions of AFSA based on different constraint-handling methods. This study is also meaningful for solving other constrained problems.

Due to the recent progress made in camera and network environments, on-line video services enable people around the world to watch or share high-quality HD videos that can record a wider angle without losing objects' details in each image. As a result, users of these services can watch videos in different ways with different ROIs (Regions of Interest), especially when there are multiple objects in a scene, and thus there are few common ways for them to transfer their impressions for each scene directly. Posting messages is currently the usual way but it does not sufficiently enable all users to transfer their impressions. To transfer a user's impressions directly and provide users with a richer video watching experience, we propose a system that enables them to extract their favorite parts of videos as ROI trajectories through simple and intuitive manipulation of their tablet device. It also enables them to share a recorded trajectory with others after stabilizing it in a manner that should be satisfactory to every user. Using statistical analysis of user manipulations, we have demonstrated an approach to trajectory stabilization that can eliminate undesirable or uncomfortable elements due to tablet-specific manipulations. The system's validity has been confirmed by subjective evaluations.

Power consumption has become a critical factor for embedded systems, especially for battery powered ones. Caches in these systems consume a large portion of the whole chip power. Embedded systems usually adopt set-associative caches to get better performance. However, parallel accessed cache ways incur more energy dissipation. This paper proposed a region-based way-partitioning scheme to reduce cache way access, and without sacrificing performance, to reduce the cache power consumption. The stack accesses and non-stack accesses are isolated and redirected to different ways of the L1 data cache. Under way-partitioning, cache way accesses are reduced, as well as the memory reference interference. Experimental results show that the proposed approach could save around 27.5% of L1 data cache energy on average, without significant performance degradation.

Passive-blind image forensics is a technique that judges whether an image is forged in the absence of watermarking. In image forgery, region duplication is a simple and widely used method. In this paper, we proposed a novel method to detect image region duplication using the spin image which is an intensity-based and rotation invariant descriptor. The method can detect region duplication exactly and is robust to geometric transformations. Furthermore, it is superior to the popular SIFT-based detection method when the copied patch is from smooth background. The experiments have proved the method's effectiveness.

UWB (Ultra Wideband) radar offers great promise for advanced near field sensors due to its high range resolution. In particular, it is suitable for rescue or resource exploration robots, which need to identify a target in low visibility or acoustically harsh environments. Recently, radar algorithms that actively coordinate multiple scattered components have been developed to enhance the imaging range beyond what can be achieved by synthesizing a single scattered component. Although we previously developed an accurate algorithm for imaging shadow regions with low computational complexity using derivatives of observed ranges for double scattered signals, the algorithm yields inaccurate images under the severe interference situations that occur with complex-shaped or multiple objects or in noisy environments. This is because small range fluctuations arising from interference or random noises can produce non-negligible image degradation owing to inaccuracy in the range derivative calculation. As a solution to this difficulty, this paper proposes a novel imaging algorithm that does not use the range derivatives of doubly scattered signals, and instead extracts a feature of expansive distributions of the observed ranges, using a unique property inherent to the doubly scattering mechanism. Numerical simulation examples of complex-shaped or multiple targets are presented to demonstrate the distinct advantage of the proposed algorithm which creates more accurate images even for complicated objects or in noisy situations.

In this paper, we study four simple but fundamental cooperative protocols operating in the decode-and-forward (DF) fashion. Intuitively, finding an appropriate relay for such protocols may greatly improve the outage performance in practice. To this end, we investigate the issue of relay selection in this paper. Specifically, using the asymptotic outage probability, we define and derive the cooperative gain (CG) which quantitatively evaluates the superiority of cooperation over direct transmission. To simplify the process of relay selection, we derive the cooperative region (CR) where a relay is necessarily invoked to aid the communication from source to destination. With the aid of CG and CR, we propose our relay selection algorithm requiring the geographical information rather than the instantaneous channel state information (CSI), and predict the optimal relay locations. In addition, two diversity bounds are also prepared and compared. Finally, both simulations and numerical results are provided on the asymptotic outage probability, CG and CR.

Existing salient object detection methods either simply use a threshold to detect desired salient objects from saliency map or search the most promising rectangular window covering salient objects on the saliency map. There are two problems in the existing methods: 1) The performance of threshold-dependent methods depends on a threshold selection and it is difficult to select an appropriate threshold value. 2) The rectangular window not only covers the salient object but also contains background pixels, which leads to imprecise salient object detection. For solving these problems, a novel saliency threshold-free method for detecting the salient object with a well-defined boundary is proposed in this paper. We propose a novel window search algorithm to locate a rectangular window on our saliency map, which contains as many as possible pixels belonging the salient object and as few as possible background pixels. Once the window is determined, GrabCut is applied to extract salient object with a well-defined boundary. Compared with existing methods, our approach doesn't need any threshold to binarize the saliency map and additional operations. Experimental results show that our approach outperforms 4 state-of-the-art salient object detection methods, yielding higher precision and better F-Measure.

This paper is concerned with coding theorems in the optimistic sense for separate coding of two correlated general sources X1 and X2. We investigate the achievable rate region Ropt (X1,X2) such that the decoding error probability caused by two encoders and one decoder can be arbitrarily small infinitely often under a certain rate constraint. We give an inner and an outer bounds of Ropt (X1,X2), where the outer bound is described by using new information-theoretic quantities. We also give two simple sufficient conditions under which the inner bound coincides with the outer bound.

Source coding with a helper is one of the most fundamental fixed-length source coding problem for correlated sources. For this source coding, Wyner and Ahlswede-Korner showed the achievable rate region which is the set of rate pairs of encoders such that the probability of error can be made arbitrarily small for sufficiently large block length. However, their expression of the achievable rate region consists of the sum of indefinitely many sets. Thus, their expression is not useful for computing the achievable rate region. This paper deals with correlated sources whose conditional distribution is related by a binary-input output-symmetric channel, and gives a parametric form of the achievable rate region in order to compute the region easily.

This paper introduces new FPGA design of user-monitoring system for power management of PC display. From the camera readings the system detects whether the user looks at the screen or not and produces signals to control the display backlight. The system provides over 88% eye detection accuracy at 8f/s image processing rate. We describe new eye-tracking algorithm and hardware and present the results of its experimental evaluation in prototype display power management system.

In this letter, distributed source coding with one distortion criterion and correlated messages is considered. This problem can be regarded as “Berger-Yeung problem with correlated messages”. It corresponds to the source coding part of the graph-based framework for transmission of a pair of correlated sources over the multiple-access channel where one is lossless and the other is lossy. As a result, the achievable rate-distortion region for this problem is provided. A rigorous proof of both achievability and converse part is also given.