Abstract—We present a novel object detection strategy using depth cue which is robust to small-sized objects. In practical
cases, the target objects that we want to detect often appear in very small portion of the input images and most of previous
object recognition and detection approaches aiming to achieve high accuracy for several object databases are not applicable. Adopting the depth cue as a prior removes the scale ambiguity and allows us to use adaptive scales for all candidate regions even when the object is seen at small size in the image. The depth cue can be easily obtained by a Laser Range Finder (LRF) or a stereo camera which have become common for many camera-based configurations. We design an experiment with a scenario in which an indoor mobile robot tries to find several target objects in general environment. The experimental result demonstrates that the proposed method is effective to improve the success rate of small object detection tasks.