We describe an empirical study on the feature space of interest points for natural images. Although local features have been widely used in image analysis as building blocks of various algorithms, there is still a lack of study on the space of local features, in particular the distributions of local features extracted from the locations of interest points. Based on an approximate neighborhood probing scheme, we devise an efficient representation that is not only helpful in visualizing the distributions of local features, but also effective in modeling the neighborhood structures of local features for fast matching. We present various experimental results that provide useful insights into feature description and fast image matching.
Abstract. The frequent change of network topology in mobile ad-hoc network leads to the stability and reliability problems of routing. Many routing schemes such as multi-path routing and backup path routing are proposed to increase the link reliability. Multi-path routing protocols usually concentrate on load balancing or disjoint routing. However, the problem of packet loss caused by re-routing from the source to the destination is ignored. In this paper, we propose the Dynamic AODV Backup Routing Protocol (DABR) to enhance the Ad hoc on-Demand Distance Vector (AODV) routing in dense mobile ad-hoc networks. The DABR follows the route discovery mechanism of AODV and dynamically calculates the backup routes. Upon the failure of primary route, data packets can be salvaged by redirecting them to the backup routes. The simulation results show that the link reliability of DABR is higher than the conventional AODV while the overhead is controlled.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.