Redundancy filtering and fusion verification for video copy detection

Multimedia Systems - Recently, the frame fusion based video copy detection scheme provides a possibility to detect copies in a continuous query video stream. However, its computational complexity...     

S1000D标准下数据模块发布样式的研究

为促进S1000D标准在以信息化为中心的综合保障技术中的应用,提高装备技术文档制作和发布的正确性和效率,文章研究了S1000D标准对PDF格式发布样式的规定,分析了XSL的工作原理和各类技术信息的Schema模式,利用XSL-FO技术编写了把数据模块发布成PDF格式的XML文档,通过XMLSPY实现了技术文档的发布;通过实例展示了实现规定的发布样式的关键技术以及从数据模块到PDF发布样式的显示效果,证明了所用方法的正确性与实用性,为实现S1000D标准下的技术信息发布提供了新的可行方法.     

Floc architecture of bioflocculation sediment by ESEM and CLSM

Sediment flocculation is a critical component for the understanding of cohesive sediment dynamics. Traditionally, the referred study has largely been devoted to forming mechanism, influencing factors and physicochemical sediment conditions of all kinds of organic-flocculation and inorganic-flocculation. However, during the last decade, the bioflocculation of sediment by biological activity has been given increasing attention. But most studies have focused on the interrelations between biological and sedimentological variables. With the assistance of a newly developed field kit and correlative microscopy (which includes environmental scanning electron microscopy and confocal laser scanning microscopy), this article begins to bridge the resolution gap between sediment particles and biological activities as well as its metabolic products biofilm, in order to better understand the role of polymeric material biofilm in floc ultrastructure and outward floc behavior of bioflocculation sediment. Results have demonstrated that bioflocculation sediment was observed to be composed of complex networks of biofilm and appeared to be of complicated physical floc structures. The biofilm was found to embed particles and permeate the void space, representing the dominant physical bridging mechanism of the flocs and contributed to the extensive surface area, architecture characteristics, and mechanical properties of bioflocculation sediment.     

Evaluating Social Navigation Visualization in Online Geographic Maps

Social navigation enables emergent collaboration between independent collaborators by exposing the behavior of each individual. This is a powerful idea for web-based visualization, where the work of one user can inform other users interacting with the same visualization. Results from a crowdsourced user study evaluating the value of such social navigation cues for a geographic map service are presented. Results show significantly improved performance for participants who interacted with the map when the visual footprints of previous users were visible.     

Occlusion cues for image scene layering

To bring computer vision closer to human vision, we attempt to enable computer to understand the occlusion relationship in an image. In this paper, we propose five low dimensional region-based occlusion cues inspired by the human perception of occlusion. These cues are semantic cue, position cue, compactness cue, shared boundary cue and junction cue. We apply these cues to predict the region-wise occlusion relationship in an image and infer the layer sequence of the image scene. A preference function, trained with samples consisting of these cues, is defined to predict the occlusion relationship in an image. Then we put all the occlusion predictions into the layering algorithm to infer the layer sequence of the image scene.The experiments on rural, artificial and outdoor scene datasets show the effectiveness of our method for occlusion relationship prediction and image scene layering.     

Automated classification of touching or overlapping M-FISH chromosomes by region fusion and homolog pairing

Automated separation and classification of touching or overlapping chromosomes in a metaphase image is a critical step in computer-aided chromosome analysis. The advent of the multiplex fluorescence in situ hybridization (M-FISH) technology enables multi-spectral chromosome image with rich spectral information and DAPI image with abundant texture information. This paper presents a fusion classification scheme to improve the segmentation of overlapping and touching chromosomes. First, the texture and spectral information is fused to partition the chromosome cluster into a series of homologous regions. Then a graph-theoretical classification and pairing method is proposed to resolve any remaining ambiguity of the aforementioned separation process. Experiment results demonstrate that the proposed method outperforms conventional multi-spectral classification methods in touching and overlapping chromosome separation.