This work presents the design and experimental verification of an original system architecture aiming at recognizing gestures based solely on the hand trajectory. Self organizing feature maps are used to model spatial information while Markov models encode the temporal aspect of hand position within a trajectory. A validated classification mechanism is produced through a set of models and a committee machine setup ensures robustness as indicated by the experimental results performed.

Optical tracking systems have become particularly popular in virtual studios applications tending to substitute electromechanical ones. However, optical systems are reported to be inferior in terms of accuracy in camera motion estimation. Moreover, marker-based approaches often cause problems in image/video compositing and impose undesirable constraints on camera movement, present work introduces a novel methodology for the construction of a two-tone blue screen, which allows the localization of camera in three-dimensional (3-D) space on the basis of the captured sequence. At the same time, a novel algorithm is presented for the extraction of camera's 3-D motion parameters based on 3-D-to-two-dimensional (2-D) line correspondences. Simulated experiments have been included to illustrate the performance of the proposed system.

Over the past few years, virtual studios applications have significantly attracted the attention of the entertainment industry. Optical tracking systems for virtual sets production have become particularly popular tending to substitute electro-mechanical ones. In this work, an existing optical tracking system is revisited, in order to tackle with inherent degenerate cases; namely, reduction of the perspective projection model to the orthographic one and blurring of the blue screen. In this context, we propose a simple algorithm for 3D motion estimation under orthography using 3D-to-2D line correspondences. In addition, the watershed algorithm is employed for successful feature extraction in the presence of defocus or motion blur.