Improvements of old project

In the autumn, we created an algorithm for introducing objects (such as a chair) into a background image (for example a room) - This was done by simply finding the horizon and then calculating a vanishing point (a point in an image where real world parallell lines converge) from that, and then align the horison and vanishing point of object and background by rotating and skewing the object. The result of one test can be seen at the end of this post.

One possible thesis approach is to improve the results of this project, for example in the following ways:

Improve object angles

• Edge detection of multiple parallell lines, followed by Maximum Likelihood estimate.
• Image rectification of both object and background, thereby making all world parallell lines parallell in the images as well.

Improve blending of object into background

• Blur object edges.
• Better edge detection.
• Analyze and align illumination parameters such as color and direction, of object and background.
• Cast shadows from inserted object on background objects.

As can be seen in the image below, some more changes could of course be made - such as giving a final result in color. Another interesting approach would be to use multiple images of the same object to automatically create a 3D model in which a person could "walk around".