Tracking tools user manual

The video window should change to display the selected channel. Sliding it to the right will make images that are too dark visible so you can see where to put the tracker. This setting has no effect on tracking, only on the images shown on the screen.

To select the first spot to track, click on its center with the left mouse button. A red plus sign will appear at the location you have selected. If you want to adjust its radius, you can hold the mouse button down after you have clicked and pull the mouse away from the center; pretty soon, the radius of the disk will track the distance you have pulled the mouse from the center.

You can also adjust the radius by clicking on the number beneath the radius slider within the kernel control panel and entering it into the dialog box that appears or by moving the radius slider. When a new tracker is created it turns red to indicate that it is the active tracker; all other trackers turn blue.

To create more trackers, click on the center of each new spot with the left mouse button. The default radius of each new spot tracker will match the radius of the spot that was active when the new one is created. Each tracked spot will be labeled with an index that matches its index in the stored tracking file.

If you click with the right mouse button, the closest tracker is moved to the location you picked and it becomes the active tracker in red. By selecting different trackers using the right mouse button, you can adjust the position of each tracker one at a time. You can drag a tracker to a new location by clicking the right mouse button on top of it and then holding the button down to drag the tracker to a new location.

Note that when optimization is turned on, the tracker will always jump to the optimum location nearest the current location of the mouse cursor. You can delete an unwanted tracker by making it the active tracker click on it with the right mouse button and then pressing the delete or backspace key on the keyboard. In version 3. This will replace the plus signs with a circle around the center at twice the radius that the kernel is set to use.

Their properties are controlled using interface widgets in the kernel control panel. For tracking spots that are even in intensity, or which have uneven intensities within them but a defined circular edge, the disc kernel should be used.

The radius should be set to match the radius of the spots you wish to track. The interpolate checkbox should be set for more accuracy and cleared for more speed. For tracking spots that are brighter in the center and drop off to dim or darkest in the center and ramp up to bright , the cone kernel should be used. The setting of the interpolate check box does not matter for the cone tracker this tracker always interpolates. A parameter relevant for both the disc and cone kernel is whether the spots are dark points in a lighter background the default or lighter points in a dark background.

You should set this for the type of spot you are seeking. If the bead profile is changing over time, or if it does not fit well into one of the above categories, then the symmetric tracker should be chosen. This tracker operates by locating the minimum variance in concentric rings around the bead center. The radius should be set to be at least slighly larger than the bead that is to be tracked; setting it larger will not harm tracking except to make the program run more slowly.

It finds the least-squares fit 2D Gaussian to the area around the point, to approximate the effect of integrating an Airy pattern centered at the emitter. The technique implemented here differs from the UIUC implementation in two ways. First, it assumes a symmetric Gaussian this assumes square pixels. Second, it only fits out to four standard deviations from the center this prevents somewhat distant spots from interfering with the optimization.

The rod3 kernel is a composite kernel. This is actually a grouping of three subkernels, each of which is one of the above types. These three kernels lie along the same line and move as a unit; they seek to track bars in the image.

When this kernel box is selected, a new control panel will appear. This control panel is shown to the right, and it enables control over the length in pixels and orientation in degrees of the bar trackers. As with the radius and position controls described above, these controls change to display and control the values of the active tracker. The most successful bars may be made of cone kernels and be slightly less than the actual length of the bar on the screen.

The symmetric kernel is probably the least useful. Note that if the bars flex, this tracker may not work very well. The image kernel is an image-based kernel that can be used to track particles that are neither radially symmetric nor rods. This kernel should be used on any object for which none of the other kernels are applicable.

This image-based kernel begins by reading in an image from the first frame of the video at the specified location with width and height equal to twice the specified radius, and in each subsequent frame, it looks in X and Y for the position in the frame that best fits the initial image.

The number of frames to average over can be set with a slider; the default value of 0 just takes the original image. Setting the value larger will let the tracker adjust as the shape of the object changes,but this will also cause the tracker to drift off the visual center of the object because there is nothing to stabilize it to the original object center. If the tracked object rotates, the imageor kernel is useful, as the orientation of the tracker can be set similar to the rod3 kernel before the initial reference image is set, and when tracking in subsequent frames, the tracker will take steps in orientation as well as in X and Y, recording orientation data for each frame as well as position.

This makes the tracking run more slowly, but is more robust to bead motion between frames. It does not affect the accuracy or the style of the main optimization for the kernel, it is only used to initialize the new search location between frames.

This following can be made faster and slightly less reliable by using estimated velocity to predict where the bead will be and reducing the search area. This is only true for beads whose motion is driven by a force; using velocity estimation on Brownian motion will produce worse results.

Prediction is enabled by selecting the predict check-box. To get the tracker to reliably lock on, it is important to catch the bead when it is moving relatively slowly because the initial velocity estimate is zero velocity. Once you have selected the type of tracker to use, and have selected spots to track, check the optimize checkbox. When you do this, the trackers should all move themselves to the centers of the spots they were started on.

You can continue to add trackers using the right mouse button after you have checked the optimize button; they will try to follow the center of the spot even as you adjust their radius. The Z location will now be updated based on the spread-function stack.

These do not affect the actual tracking, but do affect how beads are located or discarded. The window will also indicate where beads would be found given the current threshold and auto-find settings. A setting of zero disables this feature, and higher numbers blur away larger and larger features.

This slider is useful in fluorescence videos where the background is non-uniform. Lost: Two tracking sensitivity sliders located on this control panel set thresholds for detection of lost tracking. A threshold setting of zero disables each feature, and is the default. If the threshold is exceeded by one or more beads while tracking, the associated bead is marked as lost. Its value is independent of the kernel being used; it works based on how different the brightess at the center of the tracked bead is from the region surrounding the bead.

In particular, it finds the mean and variance of pixel intensities at the edge of a box around the bead center that is 1.

It then compares the variance squared difference from the mean of the value at the center of the bead from the mean value of the border; if it is less than the variance times this sensitivity setting, then the bead is marked as lost. This parameter is particularly useful for fluorescence images with low backgrounds, but could also be used for dark beads on bright backgrounds. If a bead gets within this many pixels of the border, it is marked as lost.

When either of these sliders are set to 0, its dead-zone feature is disabled. When a bead becomes lost for any of the above reasons, the result depends on the setting for the radio buttons:. Found: There are also two independent tracker-finding mechanisms, one for brightfield and one for fluorescence. It places them in the locations on the screen that have the best matches for the present kernel settings, and it creates them with the present kernel settings.

The trackers will not be placed within one radius of the edge of the screen or within two radii of existing trackers. The threshold is expressed as a fraction of the total intensity in the frame; the darkest pixel is mapped to 0 and the brightest to 1. Any region of the image that is above the threshold is considered to be a candidate for a bead.

Reducing this number will make the autofind faster, but may miss spots. This will cause the program to limit its update to a small area of pixels that surrounds the active trackers.

This requires less processing and makes the update rate faster when the video is played. Calculations are done based on known orbit parameters determined at epoch. Known orbital parameters like inclination, eccentricity, argument of perigee, mean motion revolutions per day , let us track satellite for a reasonable period of time after epoch. To keep tracking software working precisely, one should update elements periodically.

For low orbiting objects altitude less than km TLE data should be updated every few days. For higher orbits, you can update your TLE every few weeks. Other important things include making your predictions as close to real time as possible by using time synchronization, and the precise coordinates of your location. You must remember that TLE data for an object that has maneuvered since the last elset is no longer any good.

Updating is most important for satellites like Progress, Soyuz, and the Space Shuttle which maneuvers often docking, deorbit, changing of orbit. Why do we track satellites? There are several reasons. One might want to observe even with the naked eye ISS passing over their home or brilliant Iridium flares. Radio amateurs use satellite tracking software to obtain the best pass for QSO with another radio amateur.

Such software can help you with your hobby, and will help you understand more about Astronomy, and Physics. So even if you're a beginner, don't hesitate to download satellite tracking software like Orbitron.

Change your home into mission control center! Orbitron - Satellite Tracking System. Click here to see postcards list.