757 research outputs found
Dendrite Tracking in Microscopic Images using Minimum Spanning Trees and Localized E-M
No full textWe describe in this document our preliminary results regarding the tracking of dendrites spreading from a neuron in confocal microscope im- ages. When using a small number of image layers, we obtain good results by combining a EM-based local estimate of the probability that an image pixel belongs to a neuron filament with the global tree properties of the complete set of dendrites. The optimal tree is obtained with a modified minimum-spanning tree procedure. We will argue that this approach extends naturally to the complete data volume and should give even better results.CVLA
Specularities as an information source in the presence of texture
No full textThe appearance of real world objects is the result of the combination of their own texture and the light rays striking them before reaching our eyes, or our camera. This appearance therefore brings very rich information about the objects shapes, materials, motions, and also about the environment that surrounds them. However, while the visual cortex of humans is extremely powerful at sorting out these different sources intricately fused in the objects appearance, it is very challenging to reproduce this capability on a computer. As a result, Computer Vision algorithms tend to make strong simplifying assumptions. For example, one may consider only objects made of Lambertian material, or untextured or static objects, or lighting environments limited to a single point source. For this thesis, we want to overcome these limitations, and be able to consider the most general case: textured objects exhibiting both Lambertian and specular reflectance, in motion in a general lighting environment. We first discuss the limits of a purely Lambertian approach, and show that specularities carry strong information, if one is able to properly exploit them. We then consider two different problems, for which we show how to use specularities even in presence of textured surfaces and uncalibrated lighting. The first problem is the recovery of photometric parameters of object surfaces as well as the lighting environment. We show how it can be done even in case of extended specularities reflections. The second problem we tackle is 3D objects tracking. This is a well-explored problem but for which specularities have never been used, and treated as noise. We show that they can actually improve accuracy to an order of magnitude that is not possible with commonly used cues such as texture alone.CVLA
What Face and Body Shapes Can Tell Us About Height.
No full textGünel S, Rhodin H, Fua P. What Face and Body Shapes Can Tell Us About Height
Motion Capture from Pan-Tilt Cameras with Unknown Orientation
No full textBachmann R, Spörri J, Fua P, Rhodin H. Motion Capture from Pan-Tilt Cameras with Unknown Orientation. In: 2019 International Conference on 3D Vision (3DV). 2019: 308-317
Gravity as a reference for estimating a person's height from video
No full textBieler D, Gunel S, Fua P, Rhodin H. Gravity as a reference for estimating a person's height from video. In: Proceedings of the IEEE/CVF international conference on computer vision. 2019: 8569-8577
PCLs: Geometry-aware Neural Reconstruction of 3D Pose with Perspective Crop Layers
No full textYu F, Salzmann M, Fua P, Rhodin H. PCLs: Geometry-aware Neural Reconstruction of 3D Pose with Perspective Crop Layers. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2021: 9064-9073
ActiveMocap: Optimized viewpoint selection for active human motion capture
No full textKiciroglu S, Rhodin H, Sinha SN, Salzmann M, Fua P. ActiveMocap: Optimized viewpoint selection for active human motion capture. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2020: 103-112
Neural Scene Decomposition for Multi-Person Motion Capture
No full textRhodin H, Constantin V, Katircioglu I, Salzmann M, Fua P. Neural Scene Decomposition for Multi-Person Motion Capture. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 2019: 7703-7713
Deformation-aware unpaired image translation for pose estimation on laboratory animals
No full textLi S, Gunel S, Ostrek M, Ramdya P, Fua P, Rhodin H. Deformation-aware unpaired image translation for pose estimation on laboratory animals. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 2020: 13158-13168
Learning Active Learning from Data
No full textIn this paper, we suggest a novel data-driven approach to active learning (AL). The key idea is to train a regressor that predicts the expected error reduction for a candidate sample in a particular learning state. By formulating the query selection procedure as a regression problem we are not restricted to working with existing AL heuristics; instead, we learn strategies based on experience from previous AL outcomes. We show that a strategy can be learnt either from simple synthetic 2D datasets or from a subset of domain-specific data. Our method yields strategies that work well on real data from a wide range of domains.CVLA
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