This paper proposes a verification-aware design methodology that provides developers with a systematic and reliable approach to performing thread-pipelining parallelization on sequential programs. In contrast to traditional design flow, a behavior-model program is constructed before parallelizing as a bridge to help developers gradually leverage the technique of thread-pipelining parallelization. The proposed methodology integrates verification mechanisms into the design flow. To demonstrate the practicality of the proposed methodology, we applied it to the parallelization of a 3D depth map generator with thread pipelining. The parallel 3D depth map generator was further integrated into a 3D video playing system for evaluation of the verification overheads of the proposed methodology and the system performance. The results show the parallel system can achieve 33.72 fps in D1 resolution and 12.22 fps in HD720 resolution through a five-stage pipeline. When verifying the parallel program, the proposed verification approach keeps the performance degradation within 23% and 21.1% in D1 and HD720 resolutions, respectively.

Stereo-view and multi-view video formats are heavily investigated topics given their vast application potential. Depth Image Based Rendering (DIBR) system has been developed to improve Multiview Video Coding (MVC). Depth image is introduced to synthesize virtual views on the decoder side in this system. Depth image is a piecewise image, which is filled with sharp contours and smooth interior. Contours in a depth image show more importance than interior in view synthesis process. In order to improve the quality of the synthesized views and reduce the bitrate of depth image, a contour based coding strategy is proposed. First, depth image is divided into layers by different depth value intervals. Then regions, which are defined as the basic coding unit in this work, are segmented from each layer. The region is further divided into the contour and the interior. Two different procedures are employed to code contours and interiors respectively. A vector-based strategy is applied to code the contour lines. Straight lines in contours cost few of bits since they are regarded as vectors. Pixels, which are out of straight lines, are coded one by one. Depth values in the interior of a region are modeled by a linear or nonlinear formula. Coefficients in the formula are retrieved by regression. This process is called interior painting. Unlike conventional block based coding method, the residue between original frame and reconstructed frame (by contour rebuilt and interior painting) is not sent to decoder. In this proposal, contour is coded in a lossless way whereas interior is coded in a lossy way. Experimental results show that the proposed Contour Based Depth map Coding (CBDC) achieves a better performance than JMVC (reference software of MVC) in the high quality scenarios.

In this letter, a new approach to segment depth-of-field (DoF) images is proposed. The methodology is based on a two-stage model of visual neuron. The first stage is a retinal filtering by means of luminance normalizing non-linearity. The second stage is a V1-like filtering using filters estimated by independent component analysis (ICA). Segmented image is generated by the response activity of the neuron measured in terms of kurtosis. Results demonstrate that the model can discriminate image parts in different levels of depth-of-field. Comparison with other methodologies and limitations of the proposed methodology are also presented.

Recent advances in 3-D technologies draw an interest on the just noticeable difference in depth (JNDD) that describes a perceptual threshold of depth differences. In this letter, we address a new application of the JNDD to the depth image enhancement. In the proposed algorithm, a depth image is first segmented into multiple layers and then the depth range of the layer is expanded if the depth difference between adjacent layers is smaller than the JNDD. Therefore, viewers can effectively perceive the depth differences between layers and thus the human depth perception can be improved. The proposed algorithm can be applied to any depth-based 3-D display applications.

In this paper, we deal with the pedestrian detection task in outdoor scenes. Because of the complexity of such scenes, generally used gradient-feature-based detectors do not work well on them. We propose to use sparse 3D depth information as an additional cue to do the detection task, in order to achieve a fast improvement in performance. Our proposed method uses a probabilistic model to integrate image-feature-based classification with sparse depth estimation. Benefiting from the depth estimates, we map the prior distribution of human's actual height onto the image, and update the image-feature-based classification result probabilistically. We have two contributions in this paper: 1) a simplified graphical model which can efficiently integrate depth cue in detection; and 2) a sparse depth estimation method which could provide fast and reliable estimation of depth information. An experiment shows that our method provides a promising enhancement over baseline detector within minimal additional time.

Silicon Mach-Zehnder interferometric (MZI) waveguide modulator incorporating the n-channel junction field-effect transistor (JFET) as a signal modulation unit was designed, fabricated, and analyzed. The proposed MZI with JFET was designed to operate based on the plasma dispersion effect in the infrared wavelength of 1550 nm. The three different modulation lengths (ML) of 500, 1000, and 2000 µm while keeping the overall MZI length constant at 1.5 cm were set as a general design rule for these 10 µm-wide MZIs under study. When the JFET was operated in an active mode by injecting approximately 50 mA current (Is) to achieve a π phase shift, the modulation efficiency of the device was measured to be η = π /(Is· L) 40π/A-mm. The temporal and frequency response measurements also demonstrate that the respectively rise and fall times measured using a high-speed photoreceiver were in the neighborhood of 8.5 and 7.5 µsec and the 3 dB roll-off frequency (f3 dB) measured was in the excess of 400 kHz.

This paper proposes an efficient adaptive depth-map coding scheme for generating virtual-view images in 3D-video. Virtual-view images can be generated by view-interpolation based on the decoded depth-map of the image. The proposed depth-map coding scheme is designed to have a new gray-coding-based bit-plane coding method for efficiently coding the depth-map images on the object-boundary areas, as well as the conventional DCT-based coding scheme (H.264/AVC) for efficiently coding the inside area images of the objects or the background depth-map images. Simulation results show that the proposed coding scheme, in comparison with the H.264/AVC coding scheme, improves the BD-rate savings 6.77%-10.28% and the BD-PSNR gains 0.42 dB-0.68 dB. It also improves the subjective picture quality of synthesized virtual-view images using decoded depth-maps.

Wireless mesh networks have been extensively studied as expandable, flexible, and inexpensive access networks to the Internet. This paper focuses on one composed of multiple access points (APs) connected through multihop wireless communications mainly by the wireless distribution system (WDS). For scalability, the proper partition of APs into multiple WDS clusters is essential, because the number of APs in one cluster is limited due to the increasing radio interference and control packets. In this paper, we formulate this WDS clustering problem and prove the NP-completeness of its decision version through reduction from a known NP-complete problem. Then, we propose its heuristic algorithm, using a greedy method and a variable depth search method, to satisfy the complex constraints while optimizing the cost function. We verify the effectiveness of our algorithm through extensive simulations, where the results confirm its superiority to the existing algorithm in terms of throughput.

We present analytical expression for inductance of a superconducting stripline, a strip sandwiched by two superconducting ground planes. In our method, we utilize the analytical formula for a perfect-conducting stripline derived by Chang in 1976. To utilize Chang's formula, we first transform the structure of a superconducting stripline into that of a perfect-conducting stripline by reducing the thicknesses of the superconducting layers. The thickness reduction is "λ coth (t/λ)" for each (upper or lower) side, where λ and t are the field penetration depth and the layer thickness, respectively. Then, we apply Chang's formula to the transformed stripline model. The calculated results are in good agreement with the numerical and experimental results.

Structured light vision systems are based on the fact that the pixel location of light in an image has a unique association with the object depth. However, their applications are mainly limited to the properties of the object surface and the lighting conditions. This paper presents a robust vision system for accurate acquisition of 3-D surface data based on optimal structured light. To achieve depth measurement for a dynamic scene, the data acquisition must be performed with only a single image. Our special arrangement makes the image of the light stripe remaining sharp while the background becomes blurred. Moreover, a dynamic programming approach is proposed to track the optimal path while the laser beam is invisible or divergent under extreme condition. The principle and necessary mathematics for implementing the algorithm are presented. The robustness of the system against uncalibrated errors is demonstrated.

An efficient multiplier design method for predetermined coefficient groups is presented based on the variation of canonic signed digit (CSD) encoding and partial product sharing. By applications to radix-24 FFT structure and the pulse-shaping filter design used in CDMA, it is shown that the proposed method significantly reduces the area, propagation delay and power consumption compared with previous methods.

In this paper, a new heuristic algorithm is proposed to optimize the power domain clustering in controlling-value-based (CV-based) power gating technology. In this algorithm, both the switching activity of sleep signals (p) and the overall numbers of sleep gates (gate count, N) are considered, and the sum of the product of p and N is optimized. The algorithm effectively exerts the total power reduction obtained from the CV-based power gating. Even when the maximum depth is kept to be the same, the proposed algorithm can still achieve power reduction approximately 10% more than that of the prior algorithms. Furthermore, detailed comparison between the proposed heuristic algorithm and other possible heuristic algorithms are also presented. HSPICE simulation results show that over 26% of total power reduction can be obtained by using the new heuristic algorithm. In addition, the effect of dynamic power reduction through the CV-based power gating method and the delay overhead caused by the switching of sleep transistors are also shown in this paper.

We present a real-time video-based rendering system using a network camera array. Our system consists of 64 commodity network cameras that are connected to a single PC through a gigabit Ethernet. To render a high-quality novel view, our system estimates a view-dependent per-pixel depth map in real time by using a layered representation. The rendering algorithm is fully implemented on the GPU, which allows our system to efficiently perform capturing and rendering processes as a pipeline by using the CPU and GPU independently. Using QVGA input video resolution, our system renders a free-viewpoint video at up to 30 frames per second, depending on the output video resolution and the number of depth layers. Experimental results show high-quality images synthesized from various scenes.

In this letter, we propose combinatorial and search construction methods of 2-D multi-weight optical orthogonal codes (OOCs) with autocorrelation 0 and crosscorrelation 1, called multi-weight single or no pulse per row (MSNPR) codes. An upper bound on the size of MSNPR codes is derived and the performance of MSNPR codes is compared to those of other OOCs in terms of the bit error rate (BER) and evaluated using blocking probability. It is also demonstrated that the MSNPR codes can be flexibly constructed for different applications, providing the scalability to optical CDMA networks.

A bit-depth scalability is proposed in an adaptive way based on modified inter-layer predictions of the spatial scalability. A simple prediction for high dynamic range (HDR) sequences is implemented to reduce the redundancy of the residual signals between the base layer which contains low dynamic range (LDR) sequences and the enhancement layer which contains HDR sequences by using scaling and offset values.

To provide the distance information of a sound source in virtual audio space, we must have some information about effective distance cues and there must be some way to handle them properly. It is well known that the conventional cues comprise loudness, spectral information, reverberation and binaural information. Some research works have shown that most of these cues can give listeners only limited distance information. Among these cues, reverberation can give listeners effective distance information, but the implementation using this cue is not a simple problem because there are no well-defined parameters and methods. This paper discusses methods to control the perceived auditory depth with the reverberation cue. A two-stepped linear envelope method and an artificial reverberator, which can control the early reflection slope of an impulse response but does not alter the reverberation time, are proposed as solutions. To validate these methods, subjective assessment was performed.

In this paper, we propose a new scheme to represent three-dimensional (3-D) dynamic scenes using a hierarchical decomposition of depth maps. In the hierarchical decomposition, we split a depth map into four types of images: regular mesh, boundary, feature point and number-of-layer (NOL) images. A regular mesh image is obtained by down-sampling a depth map. A boundary image is generated by gathering pixels of the depth map on the region of edges. For generating feature point images, we select pixels of the depth map on the region of no edges according to their influence on the shape of a 3-D surface, and convert the selected pixels into images. A NOL image includes structural information to manage the other three images. In order to render a frame of 3-D dynamic scenes, we first generate an initial surface utilizing the information of regular mesh, boundary and NOL images. Then, we enhance the initial surface by adding the depth information of feature point images. With the proposed scheme, we can represent consecutive 3-D scenes successfully within the framework of a multi-layer structure. Furthermore, we can compress the data of 3-D dynamic scenes represented by a mesh structure by a 2-D video coder.

Accurate extraction of the trap position in the oxide in deep-submicron MOSFET by RTN measurement has been investigated both theoretically and experimentally. The conventional equation based on the ratio of emission time and capture time ignores two effects, that is, the poly gate depletion effect and surface potential variation in strong inversion regime. In this paper, by including both of the two effects, we have derived a new equation which gives us more accurate information of the trap depth from the interface and the trap energy. With experimental result, we compare the trap depth obtained from the new equation and that of the conventional method.

We clarify the effective range of distance between the front and rear images of the depth-fused 3-D (DFD) visual illusion. The DFD visual illusion is perceived when two images with many edges in the front and rear frontal-parallel planes at different depths are overlapped from the viewpoint of an observer. We evaluated how the fusion of the DFD visual illusion depended on the difference in distance between the front and rear images when the distance between the two images was changed. Subjective tests clarified the cases where DFD can be applied.

This paper introduces the hardware platform of the structured light processing based on depth imaging to perform a 3D modeling of cluttered workspace for home service robots. We have discovered that the degradation of precision and robustness comes mainly from the overlapping of multiple codes in the signal received at a camera pixel. Considering the criticality of separating the overlapped codes to precision and robustness, we proposed a novel signal separation code, referred to here as "Hierarchically Orthogonal Code (HOC)," for depth imaging. The proposed HOC algorithm was implemented by using hardware platform which applies the Xilinx XC2V6000 FPGA to perform a real time 3D modeling and the invisible IR (Infrared) pattern lights to eliminate any inconveniences for the home environment. The experimental results have shown that the proposed HOC algorithm significantly enhances the robustness and precision in depth imaging, compared to the best known conventional approaches. Furthermore, after we processed the HOC algorithm implemented on our hardware platform, the results showed that it required 34 ms of time to generate one 3D image. This processing time is about 24 times faster than the same implementation of HOC algorithm using software, and the real-time processing is realized.