论文标题
基于启发式的社会传感器服务的场景重建运动
Heuristics based Mosaic of Social-Sensor Services for Scene Reconstruction
论文作者
论文摘要
我们建议基于启发式的社会传感器云服务选择和组成模型来重建镶嵌场景。所提出的方法利用众包的社交媒体图像创建图像马赛克，以在指定的位置和时间间隔重建场景。这种新颖的方法依赖于图像元数据基础上定义的一组功能来确定服务的相关性和合成性。开发新颖的启发式方法是为了滤除非相关服务。采用多种机器学习策略来产生平滑的服务组成，从而产生由地理位置和时间索引的相关图像的镶嵌图。初步分析结果证明了所提出的组成模型的可行性。
We propose a heuristics-based social-sensor cloud service selection and composition model to reconstruct mosaic scenes. The proposed approach leverages crowdsourced social media images to create an image mosaic to reconstruct a scene at a designated location and an interval of time. The novel approach relies on the set of features defined on the bases of the image metadata to determine the relevance and composability of services. Novel heuristics are developed to filter out non-relevant services. Multiple machine learning strategies are employed to produce smooth service composition resulting in a mosaic of relevant images indexed by geolocation and time. The preliminary analytical results prove the feasibility of the proposed composition model.
