“What are some good thesis topics in Computer Vision?”
This is a common question that people ask in forums – and it’s an important question to ask for two reasons:
- There’s nothing worse than starting over in research because the path you decided to take turned out to be a dead end.
- There’s also nothing worse than being stuck with a generally good topic but one that doesn’t interest you at all. A “good” thesis topic has to be one that interests you and will keep you involved and stimulated for as long as possible.
For these reasons, it’s best to do as much research as you can to avoid the above pitfalls or your days of research will slowly become torturous for you – and that would be a shame because computer vision can truly be a lot of fun 🙂
So, down to business.
The purpose of this post is to propose ways to find that one perfect topic that will keep you engaged for months (or years) to come – and something you’ll be proud to talk about amongst friends and family.
I’ll start the discussion off by saying that your search strategy for topics depends entirely on whether you’re preparing for a Master’s thesis or a PhD. The former can be more general, the latter is (nearly always) very fine-grained specific. Let’s start with undergraduate topics first.
I’ll propose here three steps you can take to assist in your search: looking at the applications of computer vision, examining the OpenCV library, and talking to potential supervisors.
Applications of Computer Vision
Computer Vision has so many uses in the world. Why not look through a comprehensive list of them and see if anything on that list draws you in? Here’s one such list I collected from the British Machine Vision Association:
autonomous vehicles (big one nowadays!)
industrial quality inspection
medical image analysis
robotics (e.g. navigation)
security and surveillance
Go through this list and work out if something stands out for you. Perhaps your family is involved in agriculture? Look up how computer vision is helping in this field! The Economist wrote a fascinating article entitled “The Future of Agriculture” in which they discuss, among other things, the use of drones to monitor crops, create contour maps of fields, etc. Perhaps Computer Vision can assist with some of these tasks? Look into this!
OpenCV is the best library out there for image and video processing (I’ll be writing a lot more about it on this blog). Other libraries do exist that do certain specific things a little better, e.g. Tracking.js, which performs things like tracking inside the browser, but generally speaking, there’s nothing better than OpenCV.
On the topic of searching for thesis topics, I recall once reading a suggestion of going through the functions that OpenCV has to offer and seeing if anything sticks out at you there. A brilliant idea. Work down the list of the OpenCV documentation. Perhaps face recognition interests you? There are so many interesting projects where this can be utilised!
Talk to potential supervisors
You can’t go past this suggestion. Every academic has ideas constantly buzzing around his head. Academics are immersed in their field of research and are always to talking to people in the industry to look for interesting projects that they could get funding for. Go and talk to the academics at your university that are involved in Computer Vision. I’m sure they’ll have at least one project proposal ready to go for you.
You should also run any ideas of yours past them that may have emerged from the two previous steps. Or at least mention things that stood out for you (e.g. agriculture). They may be able to come up with something themselves.
Well, if you’ve reached this far in your studies then chances are you have a fairly good idea of how this all works now. I won’t patronise you too much, then. But I will mention three points that I wish someone had told me prior to starting my PhD adventure:
- You should be building your research topic around a supervisor. They’ve been in the field for a long time and know where the niches and dead ends are. Use their experience! If there’s a supervisor who is constantly publishing in object tracking, then doing research with them in this area makes sense.
- If your supervisor has a ready-made topic for you, CONSIDER TAKING IT. I can’t stress this enough. Usually the first year of your PhD involves you searching (often blindly) around various fields in Computer Vision and then just going deeper and deeper into one specific area to find a niche. If your supervisor has a topic on hand for you, this means that you are already one year ahead of the crowd. And that means one year saved of frustration because searching around in a vast realm of publications can be daunting – believe me, I’ve been there.
- Avoid going into trending topics. For example, object recognition using Convolutional Neural Networks is a topic that currently everyone is going crazy about in the world of Computer Vision. This means that in your studies, you will be competing for publications with big players (e.g. Google) who have money, manpower, and computer power at their disposal. You don’t want to enter into this war unless you are confident that your supervisor knows what they’re doing and/or your university has the capabilities to play in this big league also.
Spending time looking for a thesis topic is time worth spending. It could save you from future pitfalls. With respect to undergraduate thesis topics looking at Computer Vision applications is one place to start. The OpenCV library is another. And talking to potential supervisors at your university is also a good idea.
With respect to PhD thesis topics, it’s important to take into consideration what the fields of expertise of your potential supervisors are and then searching for topics in these areas. If these supervisors have ready-made topics for you, it is worth considering them to save you a lot of time and stress in the first year or so of your studies. Finally, it’s usually good to avoid trending topics because of the people you will be competing against for publications.
But the bottom line is, devote time to finding a topic that truly interests you. It’ll be the difference between wanting to get out of bed to do more and more research in your field or dreading each time you have to walk into your Computer Science building in the morning.
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