Human Pose, Shape and Action
3D Pose from Images
2D Pose from Images
Beyond Motion Capture
Action and Behavior
Body Perception
Body Applications
Pose and Motion Priors
Clothing Models (2011-2015)
Reflectance Filtering
Learning on Manifolds
Markerless Animal Motion Capture
Multi-Camera Capture
2D Pose from Optical Flow
Body Perception
Neural Prosthetics and Decoding
Part-based Body Models
Intrinsic Depth
Lie Bodies
Layers, Time and Segmentation
Understanding Action Recognition (JHMDB)
Intrinsic Video
Intrinsic Images
Action Recognition with Tracking
Neural Control of Grasping
Flowing Puppets
Faces
Deformable Structures
Model-based Anthropometry
Modeling 3D Human Breathing
Optical flow in the LGN
FlowCap
Smooth Loops from Unconstrained Video
PCA Flow
Efficient and Scalable Inference
Motion Blur in Layers
Facade Segmentation
Smooth Metric Learning
Robust PCA
3D Recognition
Object Detection
Autonomous Robotic Manipulation
We have developed algorithms which enable an autonomous manipulation system to grasp a wide range of objects and to perform a certain number of manipulation tasks, such as drilling, using a stapler, unlocking a door with a key or changing a tire []. More generally, we are interested in providing complete integrated systems with a certain level of autonomy. The motion system of the architecture is centered around two key concepts: 1) the control of contact interaction through high performance force and impedance control and 2) the use of optimization to generate reproducible motions of high quality.
Unlike an industrial robot, such a system has to adapt to situations it has not previously encountered. Therefore, it needs to infer properties of its surroundings using sensors, learn from experience and be robust to disturbances. In the context of this project we develop algorithms which address these challenges. A few examples are:
- Data-driven grasping algorithms []
- Learning approaches for force control []
- Algorithms for reactive movement adaptation in face of disturbances [
] - 3D object tracking algorithms using a range camera []
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