Mobile object detection through client-server based vote transfer

Mobile platforms such as smart-phones and tablet computers have attained the technological capacity to perform tasks beyond their intended purposes. The steady increase of processing power has enticed researchers to attempt increasingly challenging tasks on mobile devices with appropriate modifications over their stationary counterparts. In this work we present a novel multi-frame object detection application for the mobile platform that is capable of object localization. Our work leverages the hough forest based object detector introduced by Gall et al. in [10]. In our experiments, we demonstrate that our novel, multi-frame generalization of [10] notably improves the detection performance. We test the performance of the technique in variable resolutions, the applicability to several object categories and different datasets. We implement the multi-frame detector on a mobile platform through a novel client-server framework that presents a sound and viable environment for the multi-frame detector. Finally, we study implementations of both single and multi-frame object detectors based on this client-server framework on a mobile device running the android OS.