BibSonomyburst/tag/real_timeBibSonomy RSS feed for /tag/real_time2012-02-15T12:50:19+01:00http://www.bibsonomy.org/bibtex/26d0895dfcfa2286b7497277b3ff8df4a/davefdavef2010-04-22T11:44:21+02:00VST4WSN formal real_time reliability tinyOS wsn <span class="authorEditorList"><a href="/author/Man">Th. Vallee K.L. Man</a>, and <a href="/author/Leung">H.L. Leung</a> </span> (<em>2010</em>)Thu Apr 22 11:44:21 CEST 2010TEPAWSN: A Formal Analysis Tool for Wireless Sensor Networks2010VST4WSN formal real_time reliability tinyOS wsn http://www.bibsonomy.org/bibtex/21d3d24e1b14ceb11cb40678451d73a63/davefdavef2010-04-20T15:32:22+02:00VST4WSN formal model_checking real_time runtime_checking <span class="authorEditorList"><a href="/author/Kim">Moonjoo Kim</a>, <a href="/author/Lee">Insup Lee</a>, <a href="/author/Sammapun">Usa Sammapun</a>, <a href="/author/Shin">Jangwoo Shin</a>, and <a href="/author/Sokolsky">Oleg Sokolsky</a> </span><em>Electr. Notes Theor. Comput. Sci.</em> (<em>2002</em>)Tue Apr 20 15:32:22 CEST 2010Electr. Notes Theor. Comput. Sci.4Monitoring, Checking, and Steering of Real-Time Systems.702002VST4WSN formal model_checking real_time runtime_checking inklusive SteeringActionDefinitionLanguagehttp://www.bibsonomy.org/bibtex/2b1c15cdfe6adb6324b527ab5a8eebae4/davefdavef2010-04-20T15:30:38+02:00VST4WSN model_checking probabilistic real_time runtime_checking <span class="authorEditorList"><a href="/author/Sammapun">Usa Sammapun</a>, <a href="/author/Lee">Insup Lee</a>, and <a href="/author/Sokolsky">Oleg Sokolsky</a> </span><em>RTCSA, </em><em>page 147-153. </em><em>IEEE Computer Society, </em>(<em>2005</em>)Tue Apr 20 15:30:38 CEST 2010RTCSAconf/rtcsa/2005147-153RT-MaC: Runtime Monitoring and Checking of Quantitative and Probabilistic Properties.2005VST4WSN model_checking probabilistic real_time runtime_checking dblphttp://www.bibsonomy.org/bibtex/26c91325eb773731822fbf105365d75e0/ewomantewomant2008-11-17T16:42:41+01:00folksonomy hci imported real_time <span class="authorEditorList"><a href="/author/Hsieh">Gary Hsieh</a>, <a href="/author/Lai">Jennifer Lai</a>, <a href="/author/Hudson">Scott E. Hudson</a>, and <a href="/author/Kraut">Robert Kraut</a> </span><em>CHI &#039;08: Proceeding of the twenty-sixth annual SIGCHI conference on Human factors in computing systems, </em><em>page 223--226. </em><em>New York, NY, USA, </em><em>ACM, </em>(<em>2008</em>)Mon Nov 17 16:42:41 CET 2008New York, NY, USACHI '08: Proceeding of the twenty-sixth annual SIGCHI conference on Human factors in computing systems223--226Using tags to assist near-synchronous communication2008folksonomy hci imported real_time CHI: CHI '08, Using tags to assist ...http://www.bibsonomy.org/bibtex/2017c257edb6db85edb940b1ac3bddd99/stefanostefano2007-10-23T11:17:39+02:003D analysis real_time video videoconference <span class="authorEditorList"><a href="/author/Aliaga">Daniel G. Aliaga</a>, <a href="/author/Xu">Yi Xu</a>, and <a href="/author/Popescu">Voicu Popescu</a> </span><em>Journal of Virtual Reality and Broadcasting</em> (<em>December 2006</em>)<em>ISSN 1860-2037 . </em>Tue Oct 23 11:17:39 CEST 2007Journal of Virtual Reality and BroadcastingdecISSN 1860-203710Lag Camera: A Moving Multi-Camera Array for Scene-Acquisition320063D analysis real_time video videoconference Many applications, such as telepresence, virtual reality, and interactive walkthroughs, require a three-dimensional (3D)model of real-world environments. Methods, such as lightfields, geometric reconstruction and computer vision use cameras to acquire visual samples of the environment and construct a model. Unfortunately, obtaining models of real-world locations is a challenging task. In particular, important environments are often actively in use, containing moving objects, such as people entering and leaving the scene. The methods previously listed have difficulty in capturing the color and structure of the environment while in the presence of moving and temporary occluders. We describe a class of cameras called lag cameras. The main concept is to generalize a camera to take samples over space and time. Such a camera, can easily and interactively detect moving objects while continuously moving through the environment. Moreover, since both the lag camera and occluder are moving, the scene behind the occluder is captured by the lag camera even from viewpoints where the occluder lies in between the lag camera and the hidden scene. We demonstrate an implementation of a lag camera, complete with analysis and captured environments.