Natural Language Descriptions for Video Streams

Digital images and videos collection has increased exponentially in the recent years as more and more data is avail-able in the form of personal photo albums, handheld camera videos, feature films and multilingual broadcast news videos, presenting visual data ranging from unstructured to highly structured. Today video data accounts for 80 percent of all network traffic. There is a need for qualitative filtering to find relevant information according to user requirements. Such a distillation process requires comprehensive information processing including categorisation and summarisation of multimedia resources. One approach to addressing this issue is to convert them into a more accessible form such as human language