Opencv Feature Matching Multiple Objects

It takes the descriptor of one feature in first set and is matched with all other features in second set using some distance calculation.

Opencv feature matching multiple objects. We will see how to match features in one image with others. In short we found locations of some parts of an object in another cluttered image. We shall first do some detection with static images. There are many different methods for detecting objects based on feature matching contours matching machine learning etc.

Firstly i tried to use surf algorithm to solve this problem but it finds only the image that i took from it for querying. Basics of brute force matcher. Ask question asked 3 years 4 months ago. It is a thesis done in industrial informatics department of university.

We used a queryimage found some feature points in it we took another trainimage found the features in that image too and we found the best matches among them. Active 1 year 7 months ago. Feature matching between images in opencv can be done with brute force matcher or flann based matcher. This information is sufficient to find the object exactly on the trainimage.

Brute force matcher is simple. We used a queryimage found some feature points in it we took another trainimage found the features in that image too and we found the best matches among them. It is slow since it checks match with all the features. How can i find multiple objects of one type on one image.

For example i m trying to count how many times a bottle of shampoo is placed into a market s shelf. Opencv feature matching multiple objects. This application developed using opencv 2 4 9 visual studio 2013 and visual c cli. Bf matcher matches the descriptor of a feature from one image with all other features of another image and returns the match based on the distance.

I use orb feature finder and brute force matcher opencv 3 2 0. Please describe the problem in more detail. In this article we will do simple feature matching to warm up before we start to do object detection via video analysis. Viewed 8k times 8.

We will mix up the feature matching and findhomography from calib3d module to find known objects in a complex image. Selection of a particular method and adapting it to work with multiple instances of the class depends on the application and the type of objects.