Self-driving cars reduce human error and can accomplish various missions to help people in
different fields. They have become one of the main interests in automotive research and …

This study investigates the convex optimization frameworks for accurate and fast negative
obstacle detection as well as depth estimations that are vital for real-time, superior …

The use of industrial robots in production started a rapid expansion in the 1980s, since they
had the possibility of improving productivity, being able to work for extended periods of time …

The stereo matching algorithms for binocular vision are very popular and widely applied.
However, the algorithms may have lower matching quality or higher time complexity. To …

In this paper, we present a new approach for dense stereo matching which is mainly
oriented towards the recovery of depth map of an observed scene. The extraction of depth …

In the last ten years, isovist analysis has emerged as a fundamental method for reflecting a
person's visual experience in cities and buildings. However, until now, most studies have …

The development of intelligent systems for automotive applications requires high precision
sensors to capture dynamic environments. The race to fully autonomousvehicles has …

Stereo correspondence matching is a key problem in many applications like computer and
robotic vision to determine Three-Dimensional (3D) depth information of objects which is …

Facial recognition has been an active field of imaging science. With the recent progresses in
computer vision development, it is extensively applied in various areas, especially in law …

In this paper, we present a state of the art regarding computer vision systems for the
detection and classification of human body postures. Although emotions conveyed by …