Visual Tracking Using Depth Data

TL;DR: This paper reviews the state of the art in the field of lock-in time-of-flight (ToF) cameras, their advantages, their limitations, the existing calibration methods, and the way they are being used, sometimes in combination with other sensors.

TL;DR: In this article, a system of cameras can detect the position, orientation, and movement of the user's hands and translate that information into executable commands, including instantaneous and spatial commands.

TL;DR: In this paper, a depth camera system tracks a person in physical space and evaluates the person's intent to engage with the application, such as location, stance, movement and voice data can be evaluated.

TL;DR: In this paper, an interactive table has a display surface on which a physical object is disposed, and a camera within the interactive table responds to infrared (IR) light reflected from the physical object enabling a location of the object on the display surface to be determined, so that the object can appear part of a virtual environment displayed thereon.

TL;DR: This completely revised second edition presents an introduction to statistical pattern recognition, which is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field.

TL;DR: Efficient algorithms for computing the Hausdorff distance between all possible relative positions of a binary image and a model are presented and it is shown that the method extends naturally to the problem of comparing a portion of a model against an image.

TL;DR: Experiments show that SCG is considerably faster than BP, CGL, and BFGS, and avoids a time consuming line search.

TL;DR: A neural network-based upright frontal face detection system that arbitrates between multiple networks to improve performance over a single network, and a straightforward procedure for aligning positive face examples for training.