Information fusion is a field that deals with merging multiple inputs to create a single output. Several fusion mechanisms are in place, but none can be easily adapted to accommodate for online learning using a simulator. This paper analyzes the concept of fuzzy mediation as a novel approach to the creation of a framework through simulations of controllers interacting with a controllable object...

The cooperative perception by an inter-vehicle network promises a multitude of improvements for advanced driver assistance systems. First, for the simultaneous estimation of the vehicle ego pose and the road network infrastructure, we propose a local, highly model-based fusion architecture for digital map and video information. Second, to extend the vehicle’s field of view, we include remote in...

In this paper we study the behavior of local descriptor object recognition methods with respect to 3D geometric transformations and image resolution variations. As expected performance decreases with accentuated perspective and decrease in resolution. To improve performance and robustness, we propose a scheme to fuse color and gradient local descriptors. This approach is motivated by the discri...

Robot soccer is a challenging domain for sensor fusion and object tracking techniques, due to its team oriented, fast-paced, dynamic and competitive nature. Since each robot has a limited view about the world surrounding it, the sharing of information with its teammates is often crucial in order to be ready to react to situations which might involve it in the near future. In this paper we propo...

Human-Robot Interaction (HRI) invariably involves dialogue about objects in the environment in which the agents are situated. The paper focuses on the issue of resolving discourse references to such visual objects. The paper addresses the problem using strategies for intra-modal fusion (identifying that different occurrences concern the same object), and inter-modal fusion, (relating object ref...

Please cite this article in press as: C. Stiller et a j.inffus.2011.03.005 This article focusses on the fusion of information from various automotive sensors like radar, video, and lidar for enhanced safety and traffic efficiency. Fusion is not restricted to data from sensors onboard the same vehicle but vehicular communication systems allow to propagate and fuse information with sensor data fr...

In the past decades, most object recognition systems were based on passive approaches. But in the last few years a lot of research was done in the field of active object recognition. In this context, there are several unique problems to be solved, such as the fusion of views and the selection of an optimal next viewpoint. In this paper we present an approach to solve the problem of choosing opt...

We consider the problem of information fusion frommultiple sensors of different types with the objective of improving the confidence of inference tasks, such as object classification, performed from the data collected by the sensors. We propose a novel technique based on distributed belief aggregation using a multiagent prediction market to solve this information fusion problem. To monitor the ...

Prediction markets have been shown to be a useful tool in forecasting the outcome of future events by aggregating public opinion about the event’s outcome. We consider an analogous problem of information fusion from multiple sensors of different types with the objective of improving the confidence of inference tasks, such as object classification. We develop a multi-agent prediction market-base...

In this study, additional depth images were used to enrich the information in each image pixel. Segmentation, by its nature capable process up pixel level. So, it can detect smallest part of object, even when it’s overlapped with another object. By using segmentation, main goal is be able maintain tracking longer object starts occluded until severely right before completely disappeared. Object ...