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88 results on '"Perko, Roland"'

1. A real-time algorithm for human action recognition in RGB and thermal video

Author

Fassold, Hannes, Gutjahr, Karlheinz, Weber, Anna, and Perko, Roland

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Monitoring the movement and actions of humans in video in real-time is an important task. We present a deep learning based algorithm for human action recognition for both RGB and thermal cameras. It is able to detect and track humans and recognize four basic actions (standing, walking, running, lying) in real-time on a notebook with a NVIDIA GPU. For this, it combines state of the art components for object detection (Scaled YoloV4), optical flow (RAFT) and pose estimation (EvoSkeleton). Qualitative experiments on a set of tunnel videos show that the proposed algorithm works robustly for both RGB and thermal video., Comment: Accepted for SPIE Real-Time Image Processing and Deep Learning Conference 2023

Published
2023

2. Counting people from above: Airborne video based crowd analysis

Author

Perko, Roland, Schnabel, Thomas, Fritz, Gerald, Almer, Alexander, and Paletta, Lucas

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Crowd monitoring and analysis in mass events are highly important technologies to support the security of attending persons. Proposed methods based on terrestrial or airborne image/video data often fail in achieving sufficiently accurate results to guarantee a robust service. We present a novel framework for estimating human count, density and motion from video data based on custom tailored object detection techniques, a regression based density estimate and a total variation based optical flow extraction. From the gathered features we present a detailed accuracy analysis versus ground truth measurements. In addition, all information is projected into world coordinates to enable a direct integration with existing geo-information systems. The resulting human counts demonstrate a mean error of 4% to 9% and thus represent a most efficient measure that can be robustly applied in security critical services., Comment: Part of the OAGM/AAPR 2013 proceedings (arXiv:1304.1876)

Published
2013

5. Airborne Based High Performance Crowd Monitoring for Security Applications

Author

Perko, Roland, Schnabel, Thomas, Fritz, Gerald, Almer, Alexander, Paletta, Lucas, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Kämäräinen, Joni-Kristian, editor, and Koskela, Markus, editor

Published
2013
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7. Integrating Visual Context and Object Detection within a Probabilistic Framework

Author

Perko, Roland, Wojek, Christian, Schiele, Bernt, Leonardis, Aleš, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Paletta, Lucas, editor, and Tsotsos, John K., editor

Published
2009
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9. How Computer Vision Can Help in Outdoor Positioning

Author

Steinhoff, Ulrich, Omerčević, Dušan, Perko, Roland, Schiele, Bernt, Leonardis, Aleš, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Schiele, Bernt, editor, Dey, Anind K., editor, Gellersen, Hans, editor, de Ruyter, Boris, editor, Tscheligi, Manfred, editor, Wichert, Reiner, editor, Aarts, Emile, editor, and Buchmann, Alejandro, editor

Published
2007
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18. Preface

Author

Roth, Peter M., Steinbauer, Gerald, Fraundorfer, Friedrich, Brandstötter, Mathias, and Perko, Roland

Published
2020
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26. Automated Data Annotation for 6-DoF AI-Based Navigation Algorithm Development.

Author

Baca, Javier Gibran Apud, Jantos, Thomas, Theuermann, Mario, Hamdad, Mohamed Amin, Steinbrener, Jan, Weiss, Stephan, Almer, Alexander, and Perko, Roland

Subjects
DEGREES of freedom, ALGORITHMS, ROBOTICS, DATA acquisition systems, PARAMETERS (Statistics)
Abstract

Accurately estimating the six degree of freedom (6-DoF) pose of objects in images is essential for a variety of applications such as robotics, autonomous driving, and autonomous, AI, and vision-based navigation for unmanned aircraft systems (UAS). Developing such algorithms requires large datasets; however, generating those is tedious as it requires annotating the 6-DoF relative pose of each object of interest present in the image w.r.t. to the camera. Therefore, this work presents a novel approach that automates the data acquisition and annotation process and thus minimizes the annotation effort to the duration of the recording. To maximize the quality of the resulting annotations, we employ an optimization-based approach for determining the extrinsic calibration parameters of the camera. Our approach can handle multiple objects in the scene, automatically providing ground-truth labeling for each object and taking into account occlusion effects between different objects. Moreover, our approach can not only be used to generate data for 6-DoF pose estimation and corresponding 3D-models but can be also extended to automatic dataset generation for object detection, instance segmentation, or volume estimation for any kind of object. [ABSTRACT FROM AUTHOR]

Published
2021
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33. Projected texture fusion

Author

Klopschitz, Manfred, primary, Perko, Roland, additional, Lodron, Gerald, additional, Paar, Gerhard, additional, and Mayer, Heinz, additional

Published
2017
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49. Context Driven Focus of Attention for Object Detection.

Author

Carbonell, Jaime G., Siekmann, Jörg, Paletta, Lucas, Rome, Erich, Perko, Roland, and Leonardis, Aleš

Abstract

Context plays an important role in general scene perception. In particular, it can provide cues about an object's location within an image. In computer vision, object detectors typically ignore this information. We tackle this problem by presenting a concept of how to extract and learn contextual information from examples. This context is then used to calculate a focus of attention, that represents a prior for object detection. State-of-the-art local appearance-based object detection methods are then applied on selected parts of the image only. We demonstrate the performance of this approach on the task of pedestrian detection in urban scenes using a demanding image database. Results show that context awareness provides complementary information over pure local appearance-based processing. In addition, it cuts down the search complexity and increases the robustness of object detection. [ABSTRACT FROM AUTHOR]

Published
2007
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50. Assessment of the Stereo-Radargrammetric Mapping Potential of TerraSAR-X Multibeam Spotlight Data.

Author

Raggam, Hannes, Gutjahr, Karlheinz, Perko, Roland, and Schardt, Mathias

Subjects
DIGITAL mapping, SYNTHETIC aperture radar, COHERENT radar, IMAGING systems, GEOMETRY
Abstract

TerraSAR-X can acquire image data in various resolutions down to a range of about 1 m. Moreover, the sensor can operate at various imaging beams-and thus acquire image data at different off-nadir viewing angles. These circumstances led to a stimulation of the traditional stereo-mapping approach, as TerraSAR-X image pairs became available in high resolution and in various geometric dispositions. With respect to 3-D surface mapping, TerraSAR-X stereo data processing, therefore, is a serious alternative to synthetic aperture radar interferometry, which can be addressed as the evolving mapping technique of the last decade. Within the TerraSAR-X science program of the German Aerospace Center (DLR), high-resolution multibeam data sets in Spotlight mode were acquired for several Austrian test sites. In general, three images were obtained from either ascending or descending orbits. In order to exploit the 3-D mapping accuracy of TerraSAR-X, stereo-radargrammetric mapping techniques were applied to the data sets, thereby utilizing stereo pairs as well as multi-image data sets in various dispositions. This paper focuses on one of the selected test sites and refers to the issues of 2-D and 3-D mapping-accuracy assessment as well as to surface model and vegetation-height-model generation. Validation of these products was widely restricted to visual analysis due to the lack of adequate high-quality reference products. [ABSTRACT FROM AUTHOR]

Published
2010
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