Summary
The authors define a method to include graphics to draw attention to messages, specifically the blending of two images from two different concepts. They started the paper with the beautiful example of Starbucks and summer, and how the two ideas generated the resultant image. The paper mentions that the process they used was the hybrid blend of two images into one object, which represents both the concepts effectively. The process of visual blending is defined here to be two concepts resulting in two objects and then the integration of both the objects into one, yet, making sure that both the original objects are visible. The VisiBlend system involves various steps in the entire workflow. Firstly, the users need to brainstorm associated concepts, then find images from both the concepts, followed by annotating them correctly. Finally, the algorithm chooses the images to blend and generates final images for the mix, which is evaluated by the user. It was found that the tool helped in the improvement of the resultant image.
Reflection
This is an interesting study that can be used in the field of advertisement and marketing, among others. The main attraction of the paper is that the system helps people who are novices in graphic designing. The steps are straightforward to follow, and the results showed that using the VisiBlend system proved to be more helpful. This paper essentially tries to find the similarity between images as opposed to texts.
One of the drawbacks that the users pointed out was the time taken to find relevant images to a concept. I think this problem could be mitigated if we were to even consider scenes as opposed to a single image. Various computer vision algorithms provide tools to get bounding boxes and improve image quality. This would help users save time and get components from larger images too.
I also kept on thinking about how we can extend this idea to other possible areas. One thing that comes to my mind is if we could combine images and text to find analogies between them. By combining them, I do not mean just providing a keyword and getting an image. That is what Google or any search algorithm does. However, I mean, if a user searches for a word, then gets an image they like, could we link articles to that? We could also try and find text related to the final blended image. I am not sure about the feasibility; however, this would be an interesting experiment.
Additionally, I also was intrigued to know if participants having good technical (CS background) or artistic background (Graphics) are faster in finding images. I believe that the more “internet searching” talent we have, the lesser the time.
Questions
- What other fields can this idea be extended to? Could we possibly find texts related to the blended image? For example, for New-York and night, we could find articles that talk about both the concepts. This may result in finding more images too.
- Would using complex images like scenes as opposed to only singular images help? Computer Vision algorithms can be used to get bounds boxes out of such images to get individual objects.
- Do people with better technical or graphical skills perform better?
I feel like the addition of scenes would also complicate the algorithm and the way in which to create blends. With singular images, it is easy to identify specific points and aligning them so it is not as simple. But it is definitely an interesting idea and one I would like to see implemented because this would definitely allow more variety of visual blends to be made.