Vast amount of geospatial datasets are now available through numerous public and private organizations. These datasets usually cover different areas, have different accuracy and level of details, and are usually provided in the vector data format, where the latitude and longitude of each object is clearly specified. However, there are scenarios in which the spatial attributes of the objects are...

The quick and accurate understanding of the ambient environment, which is composed of road curbs, vehicles, pedestrians, etc., is critical for developing intelligent vehicles. The road elements included in this work are road curbs and dynamic road obstacles that directly affect the drivable area. A framework for the online modeling of the driving environment using a multi-beam LIDAR, i.e., a Ve...

Vast amount of geospatial datasets are now available through numerous public and private organizations. These datasets usually cover different areas, have different accuracy and level of details, and are usually provided in the vector data format, where the latitude and longitude of each object is clearly specified. However, there are scenarios in which the spatial attributes of the objects are...

In this paper, a novel search graph approach has been developed to find a free-collision path in a complicated unknown environment. This algorithm gives the possibility to consider some constraints based on the real world path as in road or factory environments. The main feature of the proposed approach is it’s capability to deal with unknown environments. To assess the capability of this algor...

This research proposed a pedestrian detection system in an outdoor scene by a pin-hole camera with field-programmable gate array. We used two different feature descriptors included histograms of oriented gradients and local weighted pattern which were descripted the shape and textural information for the image feature of pedestrians. Semi-supervised learning with linear support vector machine w...

Model-Based Optimization (MBO) is a paradigm in which an objective function is used to express both geometric and photometric constraints on features of interest. A parametric model of a feature (such as a road, a building, or coastline) is extracted from one or more images by adjusting the model's state variables until a minimum value of the objective function is obtained. The optimization pro...