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Estimation scene geometry is an important and fundamental task in light field processing. In conventional light field, there exist homogeneous texture surfaces, which brings ambiguity and heavy computation load in estimating the depth. In this paper, we propose phase-coding structured light field (PSLF), which projects sinusoidal waveform patterns and the phase is assigned to every pixel as the code. With the EPI of PSLF, we propose a depth estimation method. To be specific, the cost is convex with respect to the inclination angle of the candidate line in the EPI, and we propose to iterate rotating the candidate line until it converges to the optimal one. In addition, to cope with problem that the candidate samples cover multiple depth layers, we propose a method to reject the outlier samples. Experimental results demonstrate that, compared with conventional LF, the proposed PSLF improves the depth quality with mean absolute error being 0.007 pixels. In addition, the proposed optimization-based depth estimation method improves efficiency obviously with the processing speed being about 2.71 times of the tradition method.

To solve the problem lack of RGB-D dataset for training, a salient object detection algorithm by cross dataset training only using RGB dataset is proposed. First, a simple convolutional neural network is designed to prediction foreground and background trained on RGB dataset MSRA10k. Then, the SLIC superpixel segmentation method is used to fuse the depth image information and cluster pixels, which can segment the edge of salient object more accurately. Finally, based on the global distribution characteristics of salient objects, superpixels are labeled using kernel probability density estimation. In order to verify the effectiveness, the proposed algorithm is compared with three newer algorithms, which has achieved better detection results in terms of PR curve, AUC and F-Measure. Experimental results show that the proposed method can improve the salient object detection of RGB-D image in the absence of RGB-D images for training.

In this paper, we propose a hybrid scheme to measure depth values for a stereo structured light system with only a single shot. We design a dual-frequency monochromatic pattern, based on which depth values are computed in three steps. Firstly, phases and coarse depth maps are computed by following the idea of Fourier transform profilometry, where a novel phase unwrapping method is proposed. Afterward, errors in coarse depth maps are detected according to cross-view geometry consistency. Finally, spatial stereo matching is conducted to refine the detected errors. Experiments demonstrate that the proposed scheme can generate accurate stereo depth maps with only one shot, which can be used in a range of real-time applications.

Concerning the fact that previous behavior recognition algorithms tend to be affected by background and illumination noise, we propose a four-channel behavior recognition algorithm based on fine-tuning deep network Dilated Residual (DRN). Our algorithm can extract more human behavior information through the high frequency grayscale channel. Specifically, we decompose video datasets into multiframe color images, and convert them to high frequency grayscale images with high-pass filtering and normalization. Then, the four-channel dataset consists of RGB and above high frequency grayscale images. The effectiveness of the algorithm is evaluated by testing the classification accuracy on Olympic Sports dataset with DRN. The result shows that the algorithm achieves 85.5% accuracy on behavior recognition, which is 3.4% higher than the TOI+SVM method.

In this paper we propose a new salient object detection method via structured label prediction. By learning appearance features in rectangular regions, our structural region representation encodes the local saliency distribution with a matrix of binary labels. We show that the linear combination of structured labels can well model the saliency distribution in local regions. Representing region saliency with structured labels has two advantages: 1) it connects the label assignment of all enclosed pixels, which produces a smooth saliency prediction; and 2) regularshaped nature of structured labels enables well definition of traditional cues such as regional properties and center surround contrast, and these cues help to build meaningful and informative saliency measures. To measure the consistency between a structured label and the corresponding saliency distribution, we further propose an adaptive label ranking algorithm using proposals that are generated by a CNN model. Finally, we introduce a K-NN enhanced graph representation for saliency propagation, which is more favorable for our task than the widely-used adjacent-graph-based ones. Experimental results demonstrate the effectiveness of our proposed method on six popular benchmarks compared with state-of-the-art approaches.

The operation mode of island microgrid is a best way to solve the problem of remote island power supply. Aiming at the coordinated optimization problem of island microgrid, taking the economic and environmental cost of the island microgrid as the object functions and considering a variety of constraints, we build a multi-sources coordinated operation optimization model which contains PV, diesel, energy storage batteries and ocean energy. A software named island microgrid DG (Distributed Generators) optimization system is designed to provide important support for the economic and environmental operation of island microgrid. The system make prediction and analysis with multi-time scale based on the data of microgrid and can solve the multi-sources coordination optimization model by IPSO (improved particle swarm optimization). The results show that the optimal scheduling scheme is reasonable and feasible.

Preserving the edges in depth compression is important for improving the synthesized view quality, this paper presents a novel edge-preserving depth up-sampling method for down/up sampling-based depth coding using both the texture and depth information. We take into account the edge similarity between depth maps and their corresponding texture images as well as the structural similarity among depth maps to build a weight model. Based on the weight model, the optimal MMSE up-sampling coefficients are estimated from the local covariance coefficients of the down-sampled depth map. Experimental results show that our proposed interpolation method for down/up sampling-based depth coding improves both the coding efficiency and synthesized view quality.

Depth edge preservation is important for improving synthesized view quality in depth map coding. A joint texture/depth edge-directed up-sampling algorithm for depth map coding is proposed in this paper. The depth up-sampling algorithm takes into account the edge similarity between depth map and corresponding texture image, and structural similarity between low resolution depth map and high resolution depth map. Based on the these characters, the optimal MMSE up sampling coefficients are estimated from the local covariance coefficients of down-sampled depth map and corresponding texture image. Experimental results show that the proposed up-sampling algorithm for depth map coding improves both depth map coding efficiency and synthesized view quality.

The effect of powdered activated carbon (PAC) on the hybrid PAC/UF (PAC applied in combination with the ultrafiltration membrane) system was investigated in this paper. Compared to UF system, in which no PAC was added, the membrane flux was improved from 58.58% to 69.59% in terms of J/J0 value for 200 minutes' filtration. In PAC/UF process, it is the fraction which cannot be adsorbed by PAC takes greater responsibility for membrane fouling, this fraction possesses the potential to cause more irreversible fouling, regardless of its low organic content. Analysis by technological apparatus revealed that the apparent molecular weight (AMW) of this fraction is less than 500Da or more than 10kDa, and the more than 10kDa part shows predominant, it is also easily retained on the membrane surface to produce fouling; Furthermore, this fraction exhibits almost positive Zeta potential, and can be preferentially absorbed by the negative membrane surface, so as to cause the relatively severe flux decline.