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An image related question defines a specific visual task that is required inorder to produce an appropriate answer. The answer may depend on a minor detailin the image and require complex reasoning and use of prior knowledge. Whenhumans perform this task, they are able to do it in a flexible and robustmanner, integrating modularly any novel visual capability with diverse optionsfor various elaborations of the task. In contrast, current approaches to solvethis problem by a machine are based on casting the problem as an end-to-endlearning problem, which lacks such abilities.  We present a different approach, inspired by the aforementioned humancapabilities. The approach is based on the compositional structure of thequestion. The underlying idea is that a question has an abstract representationbased on its structure, which is compositional in nature. The question canconsequently be answered by a composition of procedures corresponding to itssubstructures. The basic elements of the representation are logical patterns,which are put together to represent the question. These patterns include aparametric representation for object classes, properties and relations. Eachbasic pattern is mapped into a basic procedure that includes meaningful visualtasks, and the patterns are composed to produce the overall answeringprocedure.  The UnCoRd (Understand Compose and Respond) system, based on this approach,integrates existing detection and classification schemes for a set of objectclasses, properties and relations. These schemes are incorporated in a modularmanner, providing elaborated answers and corrections for negative answers. Inaddition, an external knowledge base is queried for required common-knowledge.We performed a qualitative analysis of the system, which demonstrates itsrepresentation capabilities and provide suggestions for future developments.

Understand, Compose and Respond - Answering Visual Questions by a Composition of Abstract Procedures