With the extensive application of Web technology,it becomes more and more critical of the request to thequality and reliability of Web applications. Then it is crucial to test Web applications automaticly,entirely and...With the extensive application of Web technology,it becomes more and more critical of the request to thequality and reliability of Web applications. Then it is crucial to test Web applications automaticly,entirely and thor-oughly. So we make a study of some Web testing methods and technologies. First,we discuss the necessity of Webtesting,then analyze where the faults may take place based on the architecture of the Web ,next discuss various meth-ods of Web testing in details. Then,based on the ideology of Object-Oriented,we build a model for Web testing,anddiscuss the method of doing some pertinence testing on pages when we utilize the information of statistic. At last,weintroduce some tools for white-box testing.展开更多
Indoor visual localization,i.e.,6 Degree-of-Freedom camera pose estimation for a query image with respect to a known scene,is gaining increased attention driven by rapid progress of applications such as robotics and a...Indoor visual localization,i.e.,6 Degree-of-Freedom camera pose estimation for a query image with respect to a known scene,is gaining increased attention driven by rapid progress of applications such as robotics and augmented reality.However,drastic visual discrepancies between an onsite query image and prerecorded indoor images cast a significant challenge for visual localization.In this paper,based on the key observation of the constant existence of planar surfaces such as floors or walls in indoor scenes,we propose a novel system incorporating geometric information to address issues using only pixelated images.Through the system implementation,we contribute a hierarchical structure consisting of pre-scanned images and point cloud,as well as a distilled representation of the planar-element layout extracted from the original dataset.A view synthesis procedure is designed to generate synthetic images as complementary to that of a sparsely sampled dataset.Moreover,a global image descriptor based on the image statistic modality,called block mean,variance,and color(BMVC),was employed to speed up the candidate pose identification incorporated with a traditional convolutional neural network(CNN)descriptor.Experimental results on a popular benchmark demonstrate that the proposed method outperforms the state-of-the-art approaches in terms of visual localization validity and accuracy.展开更多
文摘With the extensive application of Web technology,it becomes more and more critical of the request to thequality and reliability of Web applications. Then it is crucial to test Web applications automaticly,entirely and thor-oughly. So we make a study of some Web testing methods and technologies. First,we discuss the necessity of Webtesting,then analyze where the faults may take place based on the architecture of the Web ,next discuss various meth-ods of Web testing in details. Then,based on the ideology of Object-Oriented,we build a model for Web testing,anddiscuss the method of doing some pertinence testing on pages when we utilize the information of statistic. At last,weintroduce some tools for white-box testing.
基金supported by the National Natural Science Foundation of China under Grant Nos.62072284 and 61772318the Special Project of Science and Technology Innovation Base of Key Laboratory of Shandong Province for Software Engineering under Grant No.11480004042015。
文摘Indoor visual localization,i.e.,6 Degree-of-Freedom camera pose estimation for a query image with respect to a known scene,is gaining increased attention driven by rapid progress of applications such as robotics and augmented reality.However,drastic visual discrepancies between an onsite query image and prerecorded indoor images cast a significant challenge for visual localization.In this paper,based on the key observation of the constant existence of planar surfaces such as floors or walls in indoor scenes,we propose a novel system incorporating geometric information to address issues using only pixelated images.Through the system implementation,we contribute a hierarchical structure consisting of pre-scanned images and point cloud,as well as a distilled representation of the planar-element layout extracted from the original dataset.A view synthesis procedure is designed to generate synthetic images as complementary to that of a sparsely sampled dataset.Moreover,a global image descriptor based on the image statistic modality,called block mean,variance,and color(BMVC),was employed to speed up the candidate pose identification incorporated with a traditional convolutional neural network(CNN)descriptor.Experimental results on a popular benchmark demonstrate that the proposed method outperforms the state-of-the-art approaches in terms of visual localization validity and accuracy.
