Object recognition vs detection vs classification? What's the difference?

Question

I don't know if this the right stackexchange forum where to ask this question, please let me know if this is not the case.

I'm developing an application which given an input image containing a painting as input, it is able to tell you the title of the painting. An analogous case is: given an input image containing a building, the returned result is the name of the building.

What kind of application is this? On first impact, I would say something like "image classification". I'm not an expert on computer vision, but I always thought that "image classification" is something like "given an image, tells me what is contained in this image".

On the other hand, object detection definition seems more related to identify an object of a class (e.g. a building) and not an instance of the class itself (e.g. Great Wall):

Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos.

About Object recogntion:

Object recognition is the ability to perceive an object's physical properties (such as shape, colour and texture) and apply semantic attributes to it (such as identifying the object as an apple).

I don't really know how to classify (what a joke...) my described application. What do you think?

Calvincalvina

Answer 1

To Explain Simply: You are going to the forest and it is utter dark. All of a sudden you see thing that is different from background (pure dark). This is called Detection.

1) something is appearing which is different from your background.So you detected.

2) Now coming closer, and you identified that it is an animal. Ah.. Now you have classified/Recognised. It could be a human too.

3) Now it is coming even closer, and now you see it a deer. So, now you identified it.

So the sequence is "Detected -> Recognized/classified -> Identified'.

"Identification is the last shell, and this you could remember with your identity card that has your face ( identified), and classified as (Human).

Karlene

These explanations are really bad, in my opinion. They clarify roughly 0% of anything that needs to be clarified. In fact, object detection is currently (in many deep learning papers) used as a synonym for object localization + object classification. – Procumbent

@Procumbent Exactly. Also, Object Recognition is now considered as a discipline in CV, and hence broader term which encompasses the different techniques/algorithms of extracting relevant features and patterns in the image to achieve a desired objective: classification, localization, matching, segmentation, etc. – Chloras

Answer 2

Object detection :- detect the objects in an image. It wont give the information regarding what the object is. In other words the output of object detection is x,y, width, height of the bounding box which contains the object.

object classification :- tells what the object is, for example cat, dog car etc. In other words, in classification or recognition output will be a class label.

I'm developing an application which given an input image containing a painting as input, it is able to tell you the title of the painting. An analogous case is: given an input image containing a building, the returned result is the name of the building.

For your problem the better suited one will be 'Sketch classification'

Deherrera