Related papers: Automatic vehicle tracking and recognition from ae…
Annually, a large number of injuries and deaths around the world are related to motor vehicle accidents. This value has recently been reduced to some extent, via the use of driver-assistance systems. Developing driver-assistance systems…
This paper addresses the problem of tracking moving objects of variable appearance in challenging scenes rich with features and texture. Reliable tracking is of pivotal importance in surveillance applications. It is made particularly…
Self-supervised multi-object trackers have tremendous potential as they enable learning from raw domain-specific data. However, their re-identification accuracy still falls short compared to their supervised counterparts. We hypothesize…
Currently, there are computer vision systems that help us with tasks that would be dull for humans, such as surveillance and vehicle tracking. An important part of this analysis is to identify traffic anomalies. An anomaly tells us that…
Despite all the challenges and limitations, vision-based vehicle speed detection is gaining research interest due to its great potential benefits such as cost reduction, and enhanced additional functions. As stated in a recent survey [1],…
The capability to autonomously track a non-cooperative target is a key technological requirement for micro aerial vehicles. In this paper, we propose an output feedback control scheme based on deep reinforcement learning for controlling a…
Driver inattention is a large problem on the roads around the world. The objective of this project was to develop an eye tracking algorithm with sufficient computational efficiency and accuracy, to successfully realize when the driver was…
The development of aerial autonomy has enabled aerial robots to fly agilely in complex environments. However, dodging fast-moving objects in flight remains a challenge, limiting the further application of unmanned aerial vehicles (UAVs).…
An appearance-based robot self-localization problem is considered in the machine learning framework. The appearance space is composed of all possible images, which can be captured by a robot's visual system under all robot localizations.…
We propose a new algorithm for real-time detection and tracking of elliptic patterns suitable for real-world robotics applications. The method fits ellipses to each contour in the image frame and rejects ellipses that do not yield a good…
The current practice of manually processing features for high-dimensional and heterogeneous aviation data is labor-intensive, does not scale well to new problems, and is prone to information loss, affecting the effectiveness and…
The development of autonomous vehicles generates a tremendous demand for a low-cost solution with a complete set of camera sensors capturing the environment around the car. It is essential for object detection and tracking to address these…
Unmanned Aerial Vehicles grow more popular by the day and applications for them are crossing boundaries of science and industry, with everything from aerial photography to package delivery to disaster management benefiting from the…
In highway scenarios, an alert human driver will typically anticipate early cut-in/cut-out maneuvers of surrounding vehicles using visual cues mainly. Autonomous vehicles must anticipate these situations at an early stage too, to increase…
Unmanned aerial vehicle (UAV) is becoming increasingly important in modern civilian and military applications. However, its novel use cases is bottlenecked by conventional satellite and terrestrial localization technologies, and calling for…
The recent surge in interest in autonomous driving stems from its rapidly developing capacity to enhance safety, efficiency, and convenience. A pivotal aspect of autonomous driving technology is its perceptual systems, where core algorithms…
With the recent advances in the object detection research field, tracking-by-detection has become the leading paradigm adopted by multi-object tracking algorithms. By extracting different features from detected objects, those algorithms can…
Understanding human-object interactions is fundamental in First Person Vision (FPV). Tracking algorithms which follow the objects manipulated by the camera wearer can provide useful cues to effectively model such interactions. Despite a few…
In this paper, we present a novel vision-based framework for tracking dynamic objects using guidance laws based on a rendezvous cone approach. These guidance laws enable an unmanned aircraft system equipped with a monocular camera to…
Unmanned Aerial Vehicle (UAV) has already demonstrated its potential in many civilian applications, and the fa\c{c}ade inspection is among the most promising ones. In this paper, we focus on enabling the autonomous perception and control of…