I have a slight confusion defferentiating between object recognition and object detection. Some people say object detection is a sub-topic of object recognition? Can someone clarify the the difference between these two topics?
To the best of my knowledge.
Object Recognition is responding to the question "What is the object in the image" Whereas, Object detection is answering the question "Where is that object"?
Hope someone can illustrate the difference by also generously providing an example to each
There is not a clear answer to this in the literature and many authors give these two terms different meanings or use them interchangeably, depending on the application. If I remember correctly, Szeliski in "Computer vision: Algorithms and applications" defines them in a way similar to this:
Object detection: to notice there is an object in an image and to know where it is in the image. So, you can outline the object but you may not know what object it is.
Object (or instance) recognition: to actually say what object you have detected, and maybe providing additionally information, such as where the object is located in the 3D space.
In some applications, such as recognizing and object to grasp it with a robotic arm, the recognition is just a verification step done after a detection, so that if you are not able to recognize the object, you cannot verify the detection and discard it (because it may be a false positive). For this reason "detection" and "recognition" are used as the same task sometimes.