EthoVision 2.1: The new standard in video tracking
30 March 2001
Wageningen - EthoVision 2.1, the upgrade from EthoVision 2.0 (released in October 2000), is now available. Besides many small improvements both in functionality and in user interface this version includes the following new features:
Experiment control
Sound feedback
Visualization of noise objects
Compatible with Windows 2000 and Windows NT 4.0
Experiment control
This feature allows you to define a series of if-then statements to start or stop data acquisition automatically. In the Experiment Control dialog, you define one or more conditions and link these with a start or stop action.The condition is related to time spent, or not spent in a particular zone. A typical application for which this feature is very handy is the Morris water maze test. In this case you can set the experiment control to automatically stop the trial when the animal being tracked reaches the platform. Another example would be the tracking of insects in an olfactometer: the experiment can be stopped automatically by EthoVision when the insect has made a choice for an odor source by entering one of the arms of the device. The experiment control has been designed in such a way that you can define complex statements in an intuitive and straightforward way.
Sound feedback
With this option enabled, EthoVision will play the sound selected as your Default Sound in your Windows sound properties at each step in the acquisition procedure. When you are using EthoVision with a remote control, it can be useful to be prompted by beeps at appropriate stages in the procedure. If the computer is in a different room, you can extend the lead to your speakers, and bring them into the room with the animals (taking care that the sound is not disturbing the animals).
Visualization of noise objects
This option enables you to visualize pixels in the video image that meet the same gray scale or color criteria as your object(s), but do not belong to the object(s) you are tracking. This way you can further optimize the detection variables and get the best possible results.