Label distribution learning (LDL) is a new learning paradigm to deal with label ambiguity. Compared with traditional supervised learning scenarios, annotation with label distribution is more expensive. Direct use of existing active learning (AL) approaches, which aim to reduce the annotation cost in traditional learning, may lead to the degradation of their performance.Label distribution learning (LDL) is a new learning paradigm to deal with label ambiguity. Compared with traditional supervised learning scenarios, annotation with label distribution is more expensive. Direct use of existing active learning (AL) approaches, which aim to reduce the annotation cost in traditional learning, may lead to the degradation of their performance.[#item_full_content]