Informatics Publishing Limited

Yang Shuo ¹, Minho Kim ¹, E-Jung Choi ¹, Seoksoo Kim ²

Affiliations
1 Department of Multimedia, Hannam University, KR
2 Department of Multimedia, Hannam University, KP

Abstract

Recently, edutainment system using augmented reality and transparent displays were researched. However, in the case of edutainment system using augmented reality due to the incongruity of environment light conditions, the virtual objects can’t fit to real world environment with natural-looking. In this paper, we designed a tangible edutainment system for synthesizing a render layer which contains real world background illumination information in order to solve virtual object’s low natural-looking problem.

Keywords

Augmented Reality, Edutainment System, Illumination Environment, Natural Feature

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Yang Shuo ¹, E-Jung Choi ¹

Affiliations
1 Department of Multimedia, HanNam University, KR

Abstract

Objectives: Vehicle driving are complex action, when drivers couldn’t focus on driving the accident will happen at any moment, we build a system to help driver prevent from traffic accident. Methods/Statistical analysis: In this paper we build a system based on computer vision techniques using support vector machine training detection pattern include distance computing and alert module. At this research we use visual data instead traditional ultrasonic wave data as source data because visual data will provide more environment detail and range than sound wave can, so using the visual data make long rang driving environment alert possible. Findings: In this research we using Haar-like features as system detection feature, because Haar-like feature is a fast and stable detection feature, in the followed test this algorithm total fit our system requires. After small sample Haar-like feature test we use Support Vector Machine to training large sample for system detection pattern and it include 3 parts: pedestrian, vehicle and motorcyclist. Base on driving video sample analysis we found there’s a “hot zone” in camera that most of valuable target will appear in this area, it improved our system computing effectiveness. Application/Improvements: In research we achieve our goal, system can help driver handing complex driving environment to avoid accident happen, future research we will focus on detection accuracy and distance accuracy.

Keywords

Computer Vision, Driving Support, Object Detection, Traffic Environment Computing.

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Yang Shuo ¹, E-Jung Choi ¹

Affiliations
1 Department of Multimedia, HanNam University, KR

Abstract

Objectives: Vehicle driving are complex action, when drivers couldn’t focus on driving the accident will happen at any moment, we build a system to help driver prevent from traffic accident. Methods/Statistical analysis: In this paper we build a system based on computer vision techniques using support vector machine training detection pattern include distance computing and alert module. At this research we use visual data instead traditional ultrasonic wave data as source data because visual data will provide more environment detail and range than sound wave can, so using the visual data make long rang driving environment alert possible. Findings: In this research we using Haar-like features as system detection feature, because Haar-like feature is a fast and stable detection feature, in the followed test this algorithm total fit our system requires. After small sample Haar-like feature test we use Support Vector Machine to training large sample for system detection pattern and it include 3 parts: pedestrian, vehicle and motorcyclist. Base on driving video sample analysis we found there’s a “hot zone” in camera that most of valuable target will appear in this area, it improved our system computing effectiveness. Application/Improvements: In research we achieve our goal, system can help driver handing complex driving environment to avoid accident happen, future research we will focus on detection accuracy and distance accuracy.

Keywords

Computer Vision, Driving Support, Object Detection, Traffic Environment Computing.

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Wang Guang-Jin ¹, Kong Xiang-Yun ², Yang Shuo ²

Affiliations
1 State Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan-430071, CN
2 Kunming University of Science and Technology, Kunming-650093, CN

Abstract

In order to describe the depositional law and the mechanical properties of dry beach tailings, the paper used an indoor that the tailings in the dam exist overt classification of particle size, and the end of storehouse agglomerate fine tailings, coarse tailings exists in front of dam instead. Model of deposition distance reveals that the distribution of tailings on dry beach is affected by grain size, the initial flow velocity of pulp, gradient and so on. Mechanical test indicates that the shear strength of medium grain tailings is larger than that of fine particle, which draws a conclusion, that the larger the grain is, the better its mechanics is. And other measures such as reducing velocity of pulp, pulp density, increasing particle size taken can shorten the deposition distance of coarse tailings, improve coarsening phenomenon of dry beach. Research finding the characteristics of the tailings deposition dry beach, which provides reference for multi-scale research and distribution law of sedimentary tailings.

Keywords

Tailing Particle, Indoor Simulating Test, Deposition Rule, Mechanics Experiment.

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