The recent deployment of very large-scale camera networks consisting of fixed/moving surveillance cameras and vehicle video recorders, has led to a novel field in object tracking problem. The major goal is to detect a...
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ISBN:
(纸本)9781479900145
The recent deployment of very large-scale camera networks consisting of fixed/moving surveillance cameras and vehicle video recorders, has led to a novel field in object tracking problem. The major goal is to detect and track each vehicle within a large area, which can be applied to video forensics. For example, a suspected vehicle can be automatically identified for mining digital criminal evidences from a large amount of video data. In this paper, we propose an efficient cross-camera vehicle tracking technique via affine invariant object matching. More specifically, we formulate the problem as invariant image feature matching among different viewpoints of cameras. To achieve vehicle matching, we first extract invariant image feature based on ASIFT (affine and scale-invariant feature transform) for each detected vehicle in a camera network. Then, to improve the accuracy of ASIFT feature matching between images from different viewpoints, we propose to efficiently match feature points based on our observed spatially invariant property of ASIFT, as well as the min-hash technique. As a result, cross-camera vehicle tracking can be efficiently and accurately achieved. Experimental results demonstrate the efficacy of the proposed algorithm and the feasibility to video forensics applications.
A1 Highlights from the eleventh ISCB Student Council Symposium 2015 Katie Wilkins, Mehedi Hassan, Margherita Francescatto, Jakob Jespersen, R. Gonzalo Parra, Bart Cuypers, Dan DeBlasio, Alexander Junge, Anupama Jigish...
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A1 Highlights from the eleventh ISCB Student Council Symposium 2015 Katie Wilkins, Mehedi Hassan, Margherita Francescatto, Jakob Jespersen, R. Gonzalo Parra, Bart Cuypers, Dan DeBlasio, Alexander Junge, Anupama Jigisha, Farzana Rahman O1 Prioritizing a drug’s targets using both gene expression and structural similarity Griet Laenen, Sander Willems, Lieven Thorrez, Yves Moreau O2 Organism specific protein-RNA recognition: A computational analysis of protein-RNA complex structures from different organisms Nagarajan Raju, Sonia Pankaj Chothani, C. Ramakrishnan, Masakazu Sekijima; M. Michael Gromiha O3 Detection of Heterogeneity in Single Particle Tracking Trajectories Paddy J Slator, Nigel J Burroughs O4 3D-NOME: 3D NucleOme Multiscale Engine for data-driven modeling of three-dimensional genome architecture Przemysław Szałaj, Zhonghui Tang, Paul Michalski, Oskar Luo, Xingwang Li, Yijun Ruan, Dariusz Plewczynski O5 A novel feature selection method to extract multiple adjacent solutions for viral genomic sequences classification Giulia Fiscon, Emanuel Weitschek, Massimo Ciccozzi, Paola Bertolazzi, Giovanni Felici O6 A Systems Biology Compendium for Leishmania donovani Bart Cuypers, Pieter Meysman, Manu Vanaerschot, Maya Berg, Hideo Imamura, Jean-Claude Dujardin, Kris Laukens O7 Unravelling signal coordination from large scale phosphorylation kinetic data Westa Domanova, James R. Krycer, Rima Chaudhuri, Pengyi Yang, Fatemeh Vafaee, Daniel J. Fazakerley, Sean J. Humphrey, David E. James, Zdenka Kuncic
Current-transfer phase-control breaking is one method of paralleled breaking. This method can make up for shortcoming of sole chamber with high rated current and high rated short-current breaking current at the same t...
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Current-transfer phase-control breaking is one method of paralleled breaking. This method can make up for shortcoming of sole chamber with high rated current and high rated short-current breaking current at the same time. In addition to breaker stationary open time and computing speed of controller, the key influence factor is that controller needs accurately to compute the current-transfer time and current zero appearing moment. It will influence the best triggering moment determination of breaker driving actuator. This paper constructs its mathematical model of current transfer process. By the theory modeling with Matlab, this paper analyzes the influencing factors to current-transfer time and current zero appearing moment. From simulation procedure and result, dc component of short-circuit current and short-circuit current phase angle of contact separating moment of first open chamber, impedance parameter of paralleled circuit and arc voltage of first open chamber after contact separating both influence the current process and current zero. After breaker structure and chamber parameters are fixed, most important matter is that short-circuit current phase angle of contact separating moment of first open chamber needs to be determined accurately.
To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 1...
To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.
The widespread use of collaborative applications as a means of communication, research and collation of information, among others, has significantly accelerated the acquisition, dissemination, and especially the shari...
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Many organizations have now adopted Service Oriented Architecture （SOA） as an architectural style to help them with architecture, design and implementation of their core services and systems. Most of these organizat...
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Many organizations have now adopted Service Oriented Architecture （SOA） as an architectural style to help them with architecture, design and implementation of their core services and systems. Most of these organizations are challenged in integrating SOA style with their overall Enterprise Architecture work. This framework links an SOA style with the Enterprise Architecture （EA） methodologies to help organizations organize their SOA effort as a key part of their Enterprise Architecture. The case study demonstrates the implementation of architecture goal with organization vision in service oriented organizational structure using services that align Business with Technology. The framework is validated and has reserved the privileges of SOA and EA.
In this paper, we report a study on the differences of using a program visualization tool collaboratively or independently. We conducted a study, where students were divided randomly into two groups: the treatment gro...
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In this paper, we report a study on the differences of using a program visualization tool collaboratively or independently. We conducted a study, where students were divided randomly into two groups: the treatment group used a visualization tool called ViLLE in collaboration with another student, while the control group used the tool alone. During the study, we recorded screen captures and students' conversations. Our previous results confirmed that the treatment group outperformed the control group in the post-test in questions related to functions and in total score. Thus, we now annotated and tagged students' actions in answering the exercises, trying to find out an explanation for the difference in learning results. The results show, that the students working in collaboration spent more time answering the difficult exercises than the students working alone, and moreover, spent more time in higher level of engagement, both relatively and absolutely measured. Furthermore, we found out that the students working in pairs discussed the most when in the higher level of engagement and that almost all discussion was related to the exercise they were doing.
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