No abstract

a) Real toy tiger. By design, it is soft to touch and exhibits significant deformation behavior.(b) Deformable model of tiger scanned by our system, with haptic interaction.(c) Real clay pot, with glazed regions. The pot exhibits a variety of contact textures and sounds.(d) Virtual interaction with scanned model of pot; includes contact texture and contact sounds. Figure 1: Examples of behavior models scanned by our system AbstractWe describe a system for constructing computer models of several aspects of physical interaction behavior, by scanning the response of real objects. The behaviors we can successfully scan and model include deformation response, contact textures for interaction with force-feedback, and contact sounds. The system we describe uses a highly automated robotic facility that can scan behavior models of whole objects. We provide a comprehensive view of the modeling process, including selection of model structure, measurement, estimation, and rendering at interactive rates. The results are demonstrated with two examples: a soft stuffed toy which has significant deformation behavior, and a hard clay pot which has significant contact textures and sounds. The results described here make it possible to quickly construct physical interaction models of objects for applications in games, animation, and e-commerce.

a) Real toy tiger. By design, it is soft to touch and exhibits significant deformation behavior.(b) Deformable model of tiger scanned by our system, with haptic interaction.(c) Real clay pot, with glazed regions. The pot exhibits a variety of contact textures and sounds.(d) Virtual interaction with scanned model of pot; includes contact texture and contact sounds. Figure 1: Examples of behavior models scanned by our system AbstractWe describe a system for constructing computer models of several aspects of physical interaction behavior, by scanning the response of real objects. The behaviors we can successfully scan and model include deformation response, contact textures for interaction with force-feedback, and contact sounds. The system we describe uses a highly automated robotic facility that can scan behavior models of whole objects. We provide a comprehensive view of the modeling process, including selection of model structure, measurement, estimation, and rendering at interactive rates. The results are demonstrated with two examples: a soft stuffed toy which has significant deformation behavior, and a hard clay pot which has significant contact textures and sounds. The results described here make it possible to quickly construct physical interaction models of objects for applications in games, animation, and e-commerce.

The Thermal Infrared Visual Object Tracking challenge 2015, VOT-TIR2015, aims at comparing short-term singleobject visual trackers that work on thermal infrared (TIR) sequences and do not apply pre-learned models of object appearance. VOT-TIR2015 is the first benchmark on shortterm tracking in TIR sequences. Results of 24 trackers are presented. For each participating tracker, a short description is provided in the appendix. The VOT-TIR2015 challenge is based on the VOT2013 challenge, but introduces the following novelties: (i) the newly collected LTIR (Linköping TIR) dataset is used, (ii) the VOT2013 attributes are adapted to TIR data, (iii) the evaluation is performed using insights gained during VOT2013 and VOT2014 and is similar to VOT2015.

No abstract