Motion Object Tracking

We present the first public exhibition that uses HTC Vive and TouchDesigner to projection-map moving objects in real-time in 3D space. Our case study is an exhibition of the media artwork " The Playground ". During this exhibition we involved the public. They found small sculptural pieces that were hidden in public areas, they brought these pieces to an exhibition space and connected them onto a central sculpture. People could also take a photo of their city environment and upload it to a webpage. When a person entered the exhibition space our system projected this person's photo onto the small sculptural piece that was in their hand. Our system tracked and projected onto this piece as it moved around an exhibition area. All of the public's photos were also projection-mapped onto a co-created central sculpture. Our contribution benefits designers, artists and researchers who want to make playful experiences that involve projection-mapping moving objects in real-time in 3D physical space using relatively inexpensive, easily accessible tools.

This work presents the design and development of a
wind tracker (MOKHTAR) with implementation of Zigzag and
Spiral algorithms for detecting the wind source. For odor tracking research the Wind tracking is important. A novel wind flow and direction sensor based on an array of Evaporative Heat Rejection Devices  (EHRD)  such  as  the  ones  used  in  cooling  towers  is developed  during  the  present  work.  The  developed  sensor  is installed on the wind tracker (MOKHTAR). MOKHTAR seeks the location  of  the  wind  source  with  Zig-Zag  and  Spiral  tracking algorithms.  Both  the  Zig  Zag  and  Spiral  algorithms  are implemented and their performance is compared with respect to step  size,  time  taken  and  the  probability  of  reaching  the  wind source.  Finally,  results  of  path  monitoring  for  comparison between  the  two  algorithms  are  shown.  The  proposed  system  is used  on  a  robot  vehicle  as  the  initial  stage  of  plume  tracking activity. Moreover, the proposed wind sensor array can be used in the meteorological and environmental studies

Since the groundbreaking work of the Kalman filter in the 1960s, considerable effort has been devoted to various discrete time filters for dynamic state estimation, especially including dozens of different types of suboptimal implementations of the Bayes filters. This has been accompanied by the rapid development of simulation/approximation theories and technologies. The essence of filters is to make the best use of the observation information in time sequence based on the hidden Markov model, which however is advisable only under the premise that the modeling errors are relatively small and that the approximation used is not too much. While admitting the success of filters in many cases, this study investigates the failure cases when they are in fact ineffective for state estimation. Several classic models have shown that the straightforward observation-only (O2) inference that does not need modeling the state dynamics can perform better (in terms of both accuracy and computing speed) for estimation than filters in certain cases. Special attention has been paid to quantitatively analyze when and why a filter will not outperform the O2 inference from the information fusion perspective.
Thanks to the rapid development of advanced sensors and sensor network, the O2 inference is not only engineering friendly and computationally fast but can also be very accurate and reliable by fusing the information received from multiple sensors. The statistical attributes of the multi-sensor O2 inference are analyzed and demonstrated through simulations. In the situation with limited sensors, the O2 approach can work jointly with existing clutter filtering and data association algorithms for multi-target tracking in clutter environments. Given an adequate number of sensors, the O2 approach can employ the multi-sensor data fusion to deal with clutter and can handle the very general multi-target tracking scenario with no background information.

Background: The nuclear lamina provides structural support to the nucleus and has a central role in defining nuclear organization. Defects in its filamentous constituents, the lamins, lead to a class of diseases collectively referred to as laminopathies. On the cellular level, lamin mutations affect the physical integrity of nuclei and nucleo-cytoskeletal interactions, resulting in increased susceptibility to mechanical stress and altered gene expression. Methods: In this study we quantitatively compared nuclear deformation and chromatin mobility in fibroblasts from a homozygous nonsense LMNA mutation patient and a Hutchinson-Gilford progeria syndrome patient with wild type dermal fibroblasts, based on the visualization of mCitrine labeled telomerebinding protein TRF2 with light-economical imaging techniques and cytometric analyses. Results: Without application of external forces, we found that the absence of functional lamin A/C leads to increased nuclear plasticity on the hour and minute time scale but also to increased intranuclear mobility down to the second time scale. In contrast, progeria cells show overall reduced nuclear dynamics. Experimental manipulation (farnesyltransferase inhibition or lamin A/C silencing) confirmed that these changes in mobility are caused by abnormal or reduced lamin A/C expression. Conclusions: These observations demonstrate that A-type lamins affect both nuclear membrane and telomere dynamics. General significance: Because of the pivotal role of dynamics in nuclear function, these differences likely contribute to or represent novel mechanisms in laminopathy development.