This paper proposes a metric learning based approach for human activity recognition with two main objectives: (1) reject unfamiliar activities and (2) learn with few examples. We s...
3D human pose estimation in multi-view settings benefits from embeddings of human actions in low-dimensional manifolds, but the complexity of the embeddings increases with the num...
This paper presents a method for finding and classifying objects within real-world scenes by using the activity of humans interacting with these objects to infer the object’s i...
Patrick Peursum, Svetha Venkatesh, Geoff A. W. Wes...
This paper presents two approaches for the representation and recognition of human action in video, aiming for viewpoint invariance. The paper first presents new results using a 2...
We present a novel action recognition method which is based on combining the effective description properties of Local Binary Patterns with the appearance invariance and adaptabil...