Cross-modal hashing is the compression of high dimensional data into compact binary codes with similar binary codes for similar objects. The key ideas is to create codes for cross-modal retrieval. The constraints are :
- It has to be an N-dimensional hamming space – a binary representation with a controllable number of bits.
- The same object from different modalities has to have a similar hash code
- The space has to be similarity-preserving
(Baltrušaitis, Ahuja, and Morency, n.d.) has some good reference papers.
Baltrušaitis, Tadas, Chaitanya Ahuja, and Louis-Philippe Morency. n.d. “Multimodal Machine Learning: A Survey and Taxonomy.” http://arxiv.org/abs/1705.09406v2.