We propose the use of 3D (2D+ time) Shape Context to recognize the spatial and temporal
details inherent in human actions. We represent an action in a video sequence by a 3D point …

This work addresses the problem of real-time 3D shape based object class recognition, its
scaling to many categories and the reliable perception of categories. A novel shape …

Recent development in depth sensors opens up new challenging task in the field of
computer vision research areas, including human-computer interaction, computer games …

We consider the problem of estimating detailed 3D structure from a single still image of an
unstructured environment. Our goal is to create 3D models which are both quantitatively …

We present the major advantages of a new'object oriented'3D SLAM paradigm, which takes
full advantage in the loop of prior knowledge that many scenes consist of repeated, domain …

Ten different feature vectors are tested in a gesture recognition task which utilizes 3D data
gathered in real-time from stereo video cameras, and HMMs for learning and recognition of …

In this work we seek to move away from the traditional paradigm for 2D object recognition
whereby objects are identified in the image as 2D bounding boxes. We focus instead on: i) …

The authors introduce a surface representation for recognizing curved objects. The
approach begins by representing an object by a discrete mesh of points built from range …

Although action recognition in videos is widely studied, current methods often fail on real-
world datasets. Many recent approaches improve accuracy and robustness to cope with …

We present a revised pipe-line of the existing 3D object detection and pose estimation
framework based on point pair feature matching. This framework proposed to represent 3D …