Abstract
In the context of combining Radar and Vision sensors for a fusion application in dense city traffic situations, one of the major challenges is to be able to validate Radar targets. We take a high-level fusion approach assuming that both sensor modalities have the capacity to independently locate and identify targets of interest. In this context, Radar targets can either correspond to a Vision target - in which case the target is validated without further processing -or not. It is the latter case that drives the focus of this paper. A non-matched Radar target can correspond to some solid object which is not part of the objects of interest of the Vision sensor (such as a guard-rail) or can be caused by reflections in which case it is a ghost target which does not match any physical object in the real world. We describe a number of computational steps for the decision making of non-matched Radar targets. The computations combine both direct motion parallax measurements and indirect motion analysis - which are not sufficient for computing parallax but are nevertheless quite effective - and pattern classification steps for covering situations which motion analysis are weak or ineffective. One of the major advantages of our high-level fusion approach is that it allows the use of simpler (low cost) Radar technology to create a combined high performance system.
| Original language | English |
|---|---|
| Pages | 819-824 |
| Number of pages | 6 |
| State | Published - 2004 |
| Event | 2004 IEEE Intelligent Vehicles Symposium - Parma, Italy Duration: 14 Jun 2004 → 17 Jun 2004 |
Conference
| Conference | 2004 IEEE Intelligent Vehicles Symposium |
|---|---|
| Country/Territory | Italy |
| City | Parma |
| Period | 14/06/04 → 17/06/04 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
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