CamTrack
Well, working on a movement tracking application using HTML, CSS, and JavaScript, it allows users to capture movement in video streams or uploaded video files. The script might not yet perfect but it's quite detailed and includes various features for tracking and manipulating video playback.
for user sake, Here’s a brief overview of how the components of this script function :
Key Component
Video and Canvas Elements:
The video element displays the video feed (from camera or uploaded file), while the canvas is used for drawing movement overlays.
Control Buttons:
Various buttons allow users to start/stop tracking, play/pause the video, adjust parameters (sensitivity, frequency, tolerance), and reset snapshots.
Movement Detection:
The script detects movement by comparing the pixel data of consecutive frames using the calculateFrameDifference...y once to avoid confusion and potential errors.
Event Listeners for Sliders:
The event listeners for sliders (sensitivity, frequency, and tolerance) correctly update their values. Make sure to also update any UI elements to reflect changes as necessary.
Filtering Logic:
filterMovementPoints function is need to be ensured later that it considers edge cases where there may be no movement points or if all points fall below the max percentage threshold.
The terms listed below to relate to various metrics that could be used in contexts like image processing, machine learning, or perhaps environmental monitoring.
it hasnt have object detection yet, if the case is moving car, it cant yet define the road or the car.
Camera mess problem ----> for now is to calibrate by Tolerance level , but for further update there will be a minimum pixel detection for easier and more effective data relay or even auto calibrate for later updates
memory overload problem ---> especially for lower tolerance level (high sensitivity tracking) it can be very much energy and bandwidth needed, processor must capable for more and more weight running as long it tracking and log of tracking is run.. worst scenario is page isnt responded then blank... page refreshed with all data dont recorded
explaination:
Spot Sensitivity (px): This refers to the sensitivity of a system to detect spots or features within an image. The "px" indicates that the measurement is in pixels. A higher spot sensitivity means the system can detect smaller or less distinct spots in the image.
Spotting Frequency (sec): This refers to the frequency at which spots are detected or recorded, measured in seconds. For instance, if a system has a spotting frequency of 5 seconds, it means that it checks or updates its detection every 5 seconds.
Tolerance: In this context, tolerance usually refers to the allowable deviation from a standard or specified value. It can indicate how much variation is acceptable in spot detection or measurement before a result is considered invalid or requires re-evaluation.
Max Spot Percentage (%): This indicates the maximum allowable percentage of spots in a given area that can be detected or classified as significant. For example, if the max spot percentage is set at 20%, it means that if more than 20% of the area is identified as spots, the result may be considered problematic or inaccurate/invalid.
These metrics can be critical for ensuring accuracy and efficiency in systems that rely on detecting and analyzing features or anomalies in images or data streams.