Adaptive window search using semantic texton forests for real-time object detection

We propose a new window search method to realize real-time object detection. Our method generates windows adaptively for objects' shapes and scales to detect various size objects. It also achieves real-time window search by using fast estimation of object's location based on existence probability of an object. Experiment results demonstrate that the proposed method reduces the number of windows drastically compared with exhaustive search. Furthermore, our method reduces the processing time while maintaining recall compared with the state-of-the art method when the numbers of searched windows are same in Pascal VOC 2007 dataset.