Publicaties

Many image-based rendering (IBR) methods rely on depth estimates obtained from structured light or time-of-flight depth sensors to synthesize novel views from sparse camera networks. However, these estimates often contain missing or noisy regions, resulting in an incorrect mapping between source and target views. This situation makes the fusion process more challenging, as the visual information is misaligned, inconsistent, or missing. In this ...

Optical camera systems are commonly used to monitor patients in computer-assisted orthopedic surgery, but strong and flickering surgical lights interfere with this imaging and degrade video quality. While algorithms exist to remove the surgical light’s flicker and spotlight artifacts, no algorithm exists that can handle both simultaneously. We therefore propose the first such algorithm for the joint removal of these artifacts. The algorithm ...

Pedestrian detection systems are one of the emerging technologies due to their wide range of applications. However, due to the dynamic environments, the data obtained from a single visual sensor for these operations is not sufficient to cover all the environmental conditions, such as varying natural light, weather conditions, etc. Therefore, the use of multiple heterogeneous visual sensors for such systems is indispensable. However, this ...

BIM has become an intrinsic tool in managing building projects due to its ability to comprehensively represent information in digital form. However, using BIM as an information exchange tool is still in its infancy, particularly with regard to construction progress monitoring beyond time schedule information. The current study focuses on the development of an automated progress monitoring framework based on an IFC-based BIM and provides an ...

Radar has become a key sensor in many advanced driver assistance systems (ADAS). Due to its excellent range and Doppler resolution, low cost, and robustness against environmental conditions, it is considered an attractive sensor for detecting and tracking vulnerable road users (VRUs). In this paper, we provide a theoretical analysis of the accuracy of radar based VRU detection and tracking systems, thereby focusing on a number of specific ...

Reliability of numerous smart traffic applications are highly dependent on the accuracy of underlying road user tracker. Demand on scalability and privacy preservation pushes vision-based smart traffic applications to sense and process images on edge devices and transmit only concise information to decision/fusion nodes. One of the requirements for deploying a vision algorithm on edge devices is its ability to process captured images in real ...

This paper reveals the characteristics and effects of nonverbal behavior and human mimicry in the context of application interviews. It discloses a novel analyzation method for psychological research by utilizing machine learning. In comparison to traditional manual data analysis, machine learning proves to be able to analyze the data more deeply and to discover connections in the data invisible to the human eye. The paper describes an ...

Depth sensing has improved rapidly in recent years, which allows for structural information to be utilized in various applications, such as virtual reality, scene and object recognition, view synthesis, and 3D reconstruction. Due to the limitations of the current generation of depth sensors, the resolution of depth maps is often still much lower than the resolution of color images. This hinders applications, such as view synthesis or 3D ...

A growing interest in technologies for autonomous driving emphasizes the demand for safe and reliable perception systems in various driving conditions. The current state-of-the-art perception solutions rely on data-driven machine learning approaches, and require large amounts of annotated data to train accurate models. In this study we have identified limitations in the existing radar-based traffic datasets, and propose a richer, annotated raw ...