Leslie Casas, M.Sc.
leslie.casas@tum.de
Chair for Computer Aided Medical Procedures & Augmented Reality Fakultät für Informatik / I-16 Technische Universität München Boltzmannstraße 3 85748 Garching bei München Germany Raum MI 03.013.037 Telefon CAMP: +49 (89) 289-17077 |
Patient Pose EstimationIn this project, we investigate machine learning algorithms for the purpose of real-time 3D human pose estimation in a hospital monitoring scenario. Patients are typically covered with a blanket and the bed is cluttered with books, laptops and other everyday objects. This makes the task more challenging than background-free human pose estimation. With the constraint of day and night monitoring capacity, we have recently published a method based on depth data which will be presented at MICCAI 2016, see link to the paper below. On this project page, you can also find the used dataset and training code. For further information, please contact Felix Achilles. |
Adversarial Learning for DenoisingWe present the idea of adversarial learning for one-dimensional signal denoising. An adversarial encoder-decoder network is proposed for denoising signals, represented by a sequence of measurements. We rely on the network’s latent representation as input to the discriminator to classify the signal into clean or noisy. Aligning the noisy and clean signal distributions results in removing the signal noise. Unlike the standard GAN training, we propose a new formulation that suits to one-dimensional signal denoising. In the evaluation, we show better performance than the related approaches, such as autoencoders and recurrent neural networks, demonstrating the benefits of our adversarial encoder-decoder network in different signal and noise types. |
2018 | |
L. Casas, N. Navab, V. Belagiannis
Adversarial Signal Denoising with Encoder-Decoder Networks This works can be found at: https://arxiv.org/abs/1812.08555 (bib) |
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L. Casas, N. Navab, S. Demirci
Patient 3D body pose estimation from pressure imaging International Journal of Computer Assisted Radiology and Surgery, https://doi.org/10.1007/s11548-018-1895-3 (bib) |
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L. Casas, C. Muerwald, F. Achilles, D. Mateus, D. Huber, N. Navab, S. Demirci
Human Pose Estimation from Pressure Sensor Data Bildverarbeitung fuer die Medizin 2018, pp 285-290 (bib) |
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Title: | M.Sc. |
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Firstname: | Leslie |
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Lastname: | Casas |
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Nationality: | Blank |
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Groups: | Patient Monitoring, Computer Vision |
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Position: | Scientific Staff |
Status: | Active |
Emailbefore: | leslie.casas |
Emailafter: | tum.de |
Room: | MI 03.13.037 |
Telephone: | +49 (89) 289-17077 |
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