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Chapter and Conference Paper
Parallel Cache Prefetching for LSM-Tree Based Store: From Algorithm to Evaluation
The Log-Structured Merge-Tree has efficient writing performance and performs well in big data scenarios. An LSM-tree transforms random writes into batch sequential writes through the design of a multilayer sto...
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Article
A bus passenger re-identification dataset and a deep learning baseline using triplet embedding
Bus passenger re-identification is a special case of person re-identification, which aims to establish identity correspondence between the front door camera and the back door camera. In bus environment,it is h...
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Article
Semantic segmentation based on fusion of features and classifiers
This paper proposes a feed forward architecture algorithm using fusion of features and classifiers for semantic segmentation. The algorithm consists of three phases: Firstly, the features from hierarchical con...
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Chapter and Conference Paper
Stereo Matching Based on Density Segmentation and Non-Local Cost Aggregation
Recently, segment-tree based Non-Local cost aggregation algorithm, which can provide extremely low computational complexity and outstanding performance, has been proposed for stereo matching. The segment-tree ...
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Chapter and Conference Paper
AGO: Accelerating Global Optimization for Accurate Stereo Matching
In stereo matching, global algorithms could produce more accurate disparity estimation than aggregated ones. Unfortunately, they remain facing prohibitively high computational challenges while minimizing an en...
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Chapter and Conference Paper
SPMVP: Spatial PatchMatch Stereo with Virtual Pixel Aggregation
Stereo matching is one of the critical problems in the field of computer vision and it has been widely applied to 3D Reconstruction, Image Refocusing and etc. Recently proposed PatchMatch (PM) stereo algorithm ef...
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Article
Human action recognition on depth dataset
Human action recognition is a hot research topic; however, the change in shapes, the high variability of appearances, dynamitic background, potential occlusions in different actions and the image limit of 2D ...
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Chapter and Conference Paper
Single Face Image Super-Resolution via Multi-dictionary Bayesian Non-parametric Learning
The face image super-resolution is a domain specific problem. Human face has complex, and fixed domain specific priors, which should be detail explored in super-resolution algorithm. This paper proposes an eff...
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Chapter and Conference Paper
Online Boosting Tracking with Fragmented Model
We propose a novel method combining online boosting and fragment to overcome the drifting problem in on-line boosting tracking. We find that in previous on-line boosting method, the voting weights of the first...