Name
Abstract | ||
|---|---|---|
Bacteria reproduce simply and rapidly by doubling their contents and then splitting in two. The majority of bacteria in the human body are countered by the human immune system, however some pathogenic bacteria survive and cause disease. A small variation of bacterium size has great impact on their ability to cope with the new environment. This variation is not traceable in bacterium images as they may be less than a pixel width. In this paper, we present a method for high precision localization and dimension estimation of bacteria in microscopic images. To create a safe environment for scientist to interact with bacteria images in sterile environment a Human Computer Interaction (HCI) system is developed using Creative Interactive Gesture Camera as a touchless input device to track a user's hand gestures and translate them into the natural field of view or point of focus as well. Experiments on simulated data, shows that our method can achieve more accurate estimation of bacterium dimension in comparing with state-of-the-art sub-pixel cell outlining tool. The visualization of augmented biological data speed up the extraction of useful information. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICCVW.2013.35 | ICCVW '13 Proceedings of the 2013 IEEE International Conference on Computer Vision Workshops |
Keywords | Field | DocType |
pathogenic bacterium,bacterium size,high precision localization,safe environment,bacteria image,sterile environment,bacterium image,scientific visualization,bacterium dimension,accurate estimation,augmented biological data,new environment,gesture recognition,microorganisms,human computer interaction,data visualisation | Biological data,Computer vision,Data visualization,Pattern recognition,Visualization,Gesture,Computer science,Gesture recognition,Artificial intelligence,Pixel,Scientific visualization,Input device | Conference |
Volume | Issue | Citations |
2013 | 1 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mohammadreza Hosseini | 1 | 2 | 1.72 |
| Arcot Sowmya | 2 | 319 | 60.05 |
| Pascal Vallotton | 3 | 47 | 9.22 |
| Tomasz P. Bednarz | 4 | 38 | 22.62 |