The visible differences predictor: an algorithm for the assessment of image fidelity
Digital images and human vision
A perceptually based physical error metric for realistic image synthesis
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
"GrabCut": interactive foreground extraction using iterated graph cuts
ACM SIGGRAPH 2004 Papers
A perceptual metric for production testing
SIGGRAPH '04 ACM SIGGRAPH 2004 Sketches
A neural network implementation of a saliency map model
Neural Networks
ACM SIGGRAPH 2009 papers
Interactive image segmentation by maximal similarity based region merging
Pattern Recognition
Efficient graph cuts for multiclass interactive image segmentation
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part II
Snap & play: auto-generate personalized find-the-difference mobile game
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Region filling and object removal by exemplar-based image inpainting
IEEE Transactions on Image Processing
Hi-index | 0.00 |
Spot-the-difference is a type of puzzles, where users try to find the different parts of two perceptually similar but actually different images. We propose a semi-automatic system to produce various spot-the-difference puzzle images tagged with their difficulties from a single input image. First, we extract regions to modify from the input by our modified maximal similarity-based region merging algorithm with little user intervention and then apply a variety of image editing techniques for each region to create a modified image. We evaluate the difficulty of a pair of the input and the modified images by considering the saliency and the perceptual difference of the modified region. We provide an empirical model to estimate the time to solve a pair of the images with respect to its difficulty. We show our experimental results and quantitative user research results to evaluate the effectiveness of the proposed method.