Journal
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
Volume 24, Issue 6, Pages 1956-1968Publisher
IEEE COMPUTER SOC
DOI: 10.1109/TVCG.2017.2703853
Keywords
Photo collage; image saliency; irregular shaped packing; image classification
Categories
Funding
- National Natural Science Foundation of China [61373059, 61672279, 61472332]
- NSF of Jiangsu Province [BK20150016]
- Research Grant Council of Hong Kong [17208214]
Ask authors/readers for more resources
A new method is presented for producing photo collages that preserve content correlation of photos. We use deep learning techniques to find correlation among given photos to facilitate their embedding on the canvas, and develop an efficient combinatorial optimization technique to make correlated photos stay close to each other. To make efficient use of canvas space, our method first extracts salient regions of photos and packs only these salient regions. We allow the salient regions to have arbitrary shapes, therefore yielding informative, yet more compact collages than by other similar collage methods based on salient regions. We present extensive experimental results, user study results, and comparisons against the state-of-the-art methods to show the superiority of our method.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available