I came across a paper that is trying to classify and detect object(s) present in what they call a natural scene data-set. They have images containing objects like cars, bikes and people.
Can anyone tell me how this is different from other data-sets that contain the images of cars/bikes/people?
The site with the data-sets I am interested in is: Natural Scene Database.
For comparison, the Caltech Computational Vision data-set also contains cars and bikes from the rear and side view (with less background).
I want to know what is so special about the natural image data-set compared to the standard data-sets containing various viewpoints of cars/bikes from these set of images? Why would this natural image data-set be a bigger callenge in object detection?