Anyway, today I came across this nicely written short editorial piece in International Journal of Computer Vision titled simply Big Data. The author describes the new techniques that are now available to the area of machine/computer vision mostly driven by advances by machine translation and speech to text processing. Both these areas came into their own once large training data sets were used. And this was possible only with general advances in storing, retrieving and processing big data sets. For more details please refer to the article here.
The current state of image recognition is best illustrated by the two examples below. In the first set the learning engine was asked to choose an image in either column 1 or 2 that looked liked the image in the remaining columns (3-5) in each of the two sets. So, for first set the learning engine needed to identify a horse and in the second set a face. And as you can see the system was able to do so correctly. Of course this by does not mean that the same algorithm would be able to identify a tree if given bunch of pictures with shrubs etc. But, it s a promising start.
|Machine Vision to identify a horse and a face in a set of images|
- Rubinstein, M., Liu, C. & Freeman, W.T. Int J Comput Vis (2016) 119: 23. doi:10.1007/s11263-016-0894-5