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Sikandar Amin
Affiliation
Osram GmbH, Munich, Germany
Topic
Faster R-CNN,Object Detection,Anchor Boxes,Attention Mechanism,Average Precision Score,Bounding Box,Cholesky Decomposition,Convolutional Neural Network,Covariance Matrix,Cross-entropy Loss,Dashed Line,Detection Methods,Dimensional Vector,Direction Of Motion,Feature Maps,Fully-connected Layer,Gallery Images,Gaussian Parameters,Global Context,Ground Truth Annotations,Head Orientation,Head Pose,Hidden State,Hidden Variables,Human-human Interaction,Image Pairs,Image Pattern,Inference Time,Interval Observer,Joint Optimization,Large Image,Local Cues,Long Short-term Memory,Long-term Forecasting,Longer Time Horizon,Lookup Table,Manual Annotation,Manual Labeling,Mean Absolute Deviation,Neural Architecture Search,Object Detection Methods,Object Tracking,Observation Period,Orange Arrows,Pedestrian,Prediction Horizon,Prediction Intervals,Prior Art,Quantitative Experiments,Query Features,
Biography
Sikandar Amin received the Master's degree in communications
engineering from the Technische Universität München, Germany, in 2009. He is currently working toward the
PhD degree at the Intelligent Autonomous Systems group, Technische Universität München, Germany. Since 2013,
he has been working as a visiting researcher with the Max Planck Institute for Informatics in Saarbruken, Germany. His
research interests include computer vision and machine learning. Specifically, he is working on 2D and 3D human pose
estimation in complex scenes for higher level tasks including activity recognition and studying human emotions during
dyadic interactions in challenging real-world settings.