Unsupervised Grounding of Textual Descriptions of Object Features and Actions in Video
Alomari, Muhannad (University of Leeds) | Chinellato, Eris (University of Leeds) | Gatsoulis, Yiannis (University of Leeds) | Hogg, David C. (University of Leeds) | Cohn, Anthony G. (University of Leeds)
Learning linguistic and visual concepts from videos and textual the word blue is represented by a subset of the colour feature descriptions without having a predefined set of representations space). We will refer to the words that have visual representations is a challenging yet important task. For example, as concrete linguistic concepts (e.g. the word humans are born without the knowledge of how many representations blue has a representation in the colour space, therefore, blue for directions there are in the world, or how they is a concrete linguistic concept). We will refer to these visual are described in natural language. In some situations, it is representations as visual concepts (e.g. the blue colour better to use the 4 directions representation (front, right, left, in the colour feature space is a visual concept). Finally, we back), in others, one can use the 8 directions (front, front will use the term groundings to refer to the connections between right, right, etc.). Humans are capable of learning these different the different linguistic concepts and visual concepts.
Apr-19-2016
- Country:
- Europe > United Kingdom > England > West Yorkshire > Leeds (0.04)
- Technology:
- Information Technology > Artificial Intelligence
- Machine Learning (1.00)
- Robots (0.71)
- Information Technology > Artificial Intelligence