Published in 29th IEEE International Conference on Image Processing (ICIP), 16th -19th October, Bordeaux, France, 2022
Authorities as well as emergency and rescue services have an increasing interest in smart support systems to ensure public safety which includes in particular behavioral analysis of pedestrians by using video surveillance systems. In order to accommodate concerns … Read more
Published in Applied Sciences, 2022
The number of video cameras in public places increases due to different reasons such as detecting dangers (e.g., thefts, robberies, terrorist attacks) and security breaches in crowds. The application of video surveillance systems is sometimes evaluated ambivalently … Read more
Published in Handbuch Polizeimanagement – Polizeipolitik – Polizeiwissenschaft – Polizeipraxis. Ed.: D. Wehe, 2022
Das Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB befasst sich seit vielen Jahren mit der intelligenten Bild- und Videoauswertung im präventiv-polizeilichen und ermittlungstechnischen Bereich. Neuste Methoden der intelligenten Videoüberwachung … Read more
Published in Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops, 2021
Automatically detecting and estimating the movement of persons in real-world uncooperative scenarios is very challenging in great part due to limited and unreliably annotated data. For instance annotating a single human body pose for activity recognition requires … Read more
Published in 17th International Conference on Machine Vision and Applications (MVA), 2021
Crowd counting is an important aspect to safety monitoring at mass events and can be used to initiate safety measures in time. State-of-the-art encoder-decoder architectures are able to estimate the number of people in a scene precisely … Read more
Published in Proceedings of the 2020 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory, 2021
This work examines the suitability of a state-of-the-art human pose trackingmethod for application within surveillance scenarios and focuses on publicplaces in urban areas that tend to suffer from crowdedness, such as city centers. Starting … Read more
Published in Bartoli A., Fusiello A. (eds) Computer Vision – ECCV 2020 Workshops, 2020
Crowd counting on the drone platform is an interesting topic in computer vision, which brings new challenges such as small object inference, background clutter and wide viewpoint. However, there are few algorithms focusing on crowd counting on the drone-captured data due to the lack of comprehensive datasets. To this end, we collect a large-scale dataset and organize the Vision Meets Drone Crowd Counting Challenge (VisDrone-CC2020) in conjunction with the 16th European Conference on Computer Vision (ECCV 2020) to promote the developments … Read more
Published in Proceedings of the 2019 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory, 2020
This report presents work and results on Activity Recognition using Part Affinity Fields for real-time surveillance applications. Starting with a short introduction to the motivation, this report gives a detailed overview over the key idea … Read more
Published in Proc. SPIE 11543, Artificial Intelligence and Machine Learning in Defense Applications II, 2020
Leveraging the power of deep neural networks, single-person pose estimation has made substantial progress throughout the last years. More recently, multi-person pose estimation has also become of growing importance, mainly driven by the high demand for reliable video surveillance systems in public security. To keep up with these demands, certain efforts have been made to improve the performance of such systems, which is yet limited by the insufficient amount of available training data. This work addresses … Read more
Published in 16th IEEE International Conference on Advanced Video and Signal Based Surveillances, 2019
Anomaly detection plays in many fields of research, along with the strongly related task of outlier detection, a very important role. Especially within the context of the automated analysis of video material recorded by surveillance cameras, abnormal situations can be of very different nature. For this purpose this work investigates … Read more
Published in 16th IEEE International Conference on Advanced Video and Signal Based Surveillance, 2019
Human pose estimation has recently made significant progress with the adoption of deep convolutional neural networks and many applications have attracted tremendous interest in recent years. However, many of these applications require pose estimation for human crowds, which still is a rarely addressed problem. For this purpose this work explores methods to optimize pose estimation for human crowds, focusing … Read more
Published in Proceedings of the 2018 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory, 2019
Authorities and security services have to deal with more and more data collected during events and on public places. Two reasons for that are the rising number of huge events, as well as the expanding coverage with CCTV cameras of areas within cities. Even the number of ground crew teams, that are equipped … Read more