The amount of difference between two images is a very subjective question. There are two sub-problem, first we need to decide on a method to visually compare two images which can conclude a numerical “Difference Value”, next we need to decide on a logic that will use to cull a set of images based on such 1 to 1 comparison. The solution to this problem is to use computer vision techniques to automatically compare the photos within the series. Not to mention the inherit computer storage that consumes. For example a 5 second time lapse in 24 hours will generate 17280 photos. Culling these photos by human comparison is time consuming and unfeasible with large data set. The problem with fixed time interval capturing is that, it will generate a large percentage of no-movement photo series. A more common setup is to capture photos with a fixed time interval, this is supported by cameras like GoPro and many DSRL natively, or can be otherwise achieved with a cheap intervalometer with other cameras. In applications where a time lapse intents to capture movements in a scene, a movement triggered camera is used.
This piece of code utilizes OpenCV libraries to optimize a series of time lapse photos.
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