The random decision forests method is proposed to detect small object such as UAVs and aircrafts when they occupy a small portion of the field of view, with complex backgrounds, and are filmed by a camera that itself moves. The random decision forests is learned with discriminative decision trees, where every tree internal node is a discriminative classifier. The experimental results show that this small object detection approach achieves good object detection results.