Academic problem solving in Computer Vision
With all due respect, your question is rather vague...  For example, it is not clear to me what you mean by "structured methods of computer vision problem solving", or what you mean by a "graduate manner" of object detection or recognition.

If you are doing a Master's thesis in computer vision then presumably you have an adviser, who is supposed to be knowledgeable in this field, and who is supposed to help you define your problem, and point you to the relevant papers.

By the way, defining and constraining your problem is the key here. "general steps of solving an object detection (or recognition)" is not a very well defined problem.  Are you trying to detect a specific object, such as a particular book or your favorite coffee mug? Or are you trying to detect members of broad categories of objects, such as faces, cars, people, or chairs? 

Does your method need to be invariant to in-plane rotation?  The answer is probably "no" for faces, which are rarely upside down, but "yes" for detecting cars in aerial images.  There are many more questions like this.

So, my point is that object detection, let alone recognition, is a broad area, and it is best to talk to your adviser about scoping it down.