• Home
  • Steven Puttemans
Steven Puttemans

Steven Puttemans
Vlaams Agentschap Innoveren en Ondernemen (VLAIO) · Innovatiesteun

Doctor in Engineering Technology

About

41
Publications
15,621
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
144
Citations
Citations since 2016
24 Research Items
140 Citations
201620172018201920202021202205101520253035
201620172018201920202021202205101520253035
201620172018201920202021202205101520253035
201620172018201920202021202205101520253035
Introduction
Steven Puttemans is a post-doctoral research candidate at the KU Leuven, where he is working for the EAVISE research group, which focuses on combining computer vision and artificial intelligence. He obtained a master of science degree in Electronics-ICT and further expanded his interest in computer vision by obtaining a master of science in Artificial Intelligence. On the 13th of December 2017 he obtained his Doctor in Engineering Technology degree at the KU Leuven.

Publications

Publications (41)
Thesis
Full-text available
State-of-the-art object detection algorithms are designed to be heavily robust against scene and object variations like illumination changes, occlusions, scale changes, orientation differences, background clutter and object intra-class variability. However, in industrial machine vision applications, where objects with variable appearance have to be...
Conference Paper
Full-text available
Object detection using a boosted cascade of weak classifiers is a principle that has been used in a variety of applications, ranging from pedestrian detection to fruit counting in orchards, and this with a high average precision. In this work we prove that using both the approach suggest by Viola & Jones and the adapted approach by Dollár yields pr...
Conference Paper
Full-text available
The uprising trend of deep learning in computer vision and artificial intelligence can simply not be ignored. On the most diverse tasks, from recognition and detection to segmentation, deep learning is able to obtain state-of-the-art results, reaching top notch performance. In this paper we explore how deep convolutional neural networks dedicated t...
Conference Paper
Full-text available
Computer vision has almost solved the issue of in the wild face detection, using complex techniques like convolutional neural networks. On the contrary many open source computer vision frameworks like OpenCV have not yet made the switch to these complex techniques and tend to depend on well established algorithms for face detection, like the cascad...
Conference Paper
Full-text available
Fully automated detection and localisation of fruit in orchards are key components in creating automated robotic harvesting systems. During recent years a lot of research on this topic has been performed, either using basic computer vision techniques, like colour based segmentation, or by resorting to other sensors, like LWIR, hyperspectral or 3D....
Article
Full-text available
The extraction of permanent structures (such as walls, floors, and ceilings) is an important step in the reconstruction of building interiors from point clouds. These permanent structures are, in general, assumed to be planar. However, point clouds from building interiors often also contain clutter with planar surfaces such as furniture, cabinets,...
Preprint
Full-text available
The uprising trend of deep learning in computer vision and artificial intelligence can simply not be ignored. On the most diverse tasks, from recognition and detection to segmentation, deep learning is able to obtain state-of-the-art results, reaching top notch performance. In this paper we explore how deep convolutional neural networks dedicated t...
Preprint
Full-text available
Shopping behaviour analysis through counting and tracking of people in shop-like environments offers valuable information for store operators and provides key insights in the stores layout (e.g. frequently visited spots). Instead of using extra staff for this, automated on-premise solutions are preferred. These automated systems should be cost-effe...
Article
Full-text available
In this paper, we investigate the feasibility of automatic small object detection, such as vehicles and vessels, in satellite imagery with a spatial resolution between 0.3 and 0.5 m. The main challenges of this task are the small objects, as well as the spread in object sizes, with objects ranging from 5 to a few hundred pixels in length. We first...
Article
Full-text available
This preface acts as an introduction to the special issue on Advanced Machine Vision. It highlights the goal of this special issue on Advanced Machine Vision as well as discusses the reviewing process. On top of that, it highlights the selected submissions and describes them briefly.
Chapter
Full-text available
Shopping behaviour analysis through counting and tracking of people in shop-like environments offers valuable information for store operators and provides key insights in the stores layout (e.g. frequently visited spots). Instead of using extra staff for this, automated on-premise solutions are preferred. These automated systems should be cost-effe...
Article
Applications ranging from simple visualization to complex design require 3D models of indoor environments. This has given rise to advancements in the field of automated reconstruction of such models. In this paper, we review several state-of-the-art metrics proposed for geometric comparison of 3D models of building interiors. We evaluate their perf...
Chapter
Full-text available
For some applications it can be preferable to use images of spheres in order to calibrate a 2D camera. All published sphere-based algorithms need the complete knowledge of the elliptic sphere image, i.e. 5 geometric parameters, in particular the ellipse orientation. Because sphere images tend to be close to circular shapes, this orientation is ofte...
Chapter
Full-text available
In this paper, we propose a framework for reconstructing a compact geometric model from point clouds of building interiors. Geometric reconstruction of indoor scenes is especially challenging due to clutter in the scene, such as furniture and cabinets. The clutter may (partially) hide the structural components of the interior. The proposed framewor...
Conference Paper
Full-text available
In this paper, we propose a framework for reconstructing a compact geometric model from point clouds of building interiors. Geometric reconstruction of indoor scenes is especially challenging due to clutter in the scene, such as furniture and cabinets. The clutter may (partially) hide the structural components of the interior. The proposed framewor...
Conference Paper
Full-text available
Due to the wide applicability of pedestrian detection in surveillance and safety, this research topic has received much attention in computer vision literature. However, the focus of this research mainly lies in detecting and locating pedestrians individually as accurate as possible. In recent years, a number of datasets are captured using a forwar...
Conference Paper
Full-text available
In this work, we compare four different approaches for detecting photovoltaic installations from RGB aerial images. Our client, an electricity grid administrator, wants to hunt down fraud with unregistered illegal solar panel installations by detecting installations in aerial imagery and checking these against their database of registered installat...
Conference Paper
Full-text available
When capturing images in the wild containing pedestrians, privacy issues remain a major concern for indus- trial applications. Our application, collecting cycloramic mobile mapping data in crowded environments, is an example of this. If the data is processed and accessed by third parties, privacy of pedestrians must be ensured. This is where pedest...
Poster
Full-text available
A poster presentation of my PhD research up till that moment
Conference Paper
Full-text available
Due to the rapidly aging population, developing automated home care systems is a very important step in taking care of elderly people. This will enable us to automatically monitor the health of senior citizens in their own living environment and prevent problems before they happen. One of the challenging tasks is to actively monitor walking habits...
Conference Paper
Full-text available
The goal of this research is to investigate the possibility of using object categorization and object classification techniques in an industrial context with a very limited set of training data. As an industrial application of the proposed techniques we investigate the case of orchid flower detection and orchid species classification in an orchid p...
Presentation
Full-text available
Presenting the EAVISE research group as a whole and more specifically the research I have been doing as a PhD research assistant.
Book
Computer vision is becoming accessible to a large audience of software developers who can leverage mature libraries such as OpenCV. However, as they move beyond their first experiments in computer vision, developers may struggle to ensure that their solutions are sufficiently well optimized, well trained, robust, and adaptive in real-world conditio...
Conference Paper
Full-text available
Doctoral Consortium - PhD Research State - no abstract available
Article
Full-text available
Day-today industrial computer vision applications focusing on object detection have the need of robust, fast and accurate object detection techniques. However, current state-of-the-art object categorization techniques only reach about 85% detection rate when performing in the wild detections who try to cope with as much scene and object variation a...
Presentation
Full-text available
Presentation of my research at the Vision and Robotics 2013 congres
Conference Paper
Full-text available
State-of-the-art object categorization algorithms are designed to be heavily robust against scene variations like illumination changes, occlusions, scale changes, orientation and location differences, background clutter and object intra-class variability. However, in industrial machine vision applications where objects with variable appearance have...
Presentation
Full-text available
Presentation on the IWT-TETRA TOBCAT project

Network

Cited By