Researchers of the Computer Science and Artificial Intelligence Laboratory at MIT (Massachusetts Institute for Technology) published a pretty interesting paper about an algorithm that can determine how memorable your photos are. It’s artificial intelligence, and the algorithm can be tried out here.

From the LaMem site:

Progress in estimating visual memorability has been limited by the small scale and lack of variety of benchmark data. Here, we introduce a novel experimental procedure to objectively measure human memory, allowing us to build LaMem, the largest annotated image memorability dataset to date (containing 60,000 images from diverse sources). Using Convolutional Neural Networks (CNNs), we show that fine-tuned deep features outperform all other features by a large margin, reaching a rank correlation of 0.64, near human consistency (0.68). Analysis of the responses of the high-level CNN layers shows which objects and regions are positively, and negatively, correlated with memorability, allowing us to create memorability maps for each image and provide a concrete method to perform image memorability manipulation. This work demonstrates that one can now robustly estimate the memorability of images from many different classes, positioning memorability and deep memorability features as prime candidates to estimate the utility of information for cognitive systems.

The paper is titled Understanding and Predicting Image Memorability at a Large Scale (A. Khosla, A. S. Raju, A. Torralba and A. Oliva) and can be downloaded here.

The underlaying dataset can be explored, and the whole thing is available for download, i.e. you can get a pre-trained system and use it on your computer.

[via TDP]