Enabling Depth-driven Visual Attention on the iCub Humanoid Robot: Instructions for Use and New Perspectives

The importance of depth perception in the interactions that humans have within their nearby space is a well established fact. Consequently, it is also well known that the possibility of exploiting good stereo information would ease and, in many cases, enable, a large variety of attentional and interactive behaviors on humanoid robotic platforms. However, the difficulty of computing real-time and robust binocular disparity maps from moving stereo cameras often prevents from relying on this kind of cue to visually guide robots' attention and actions in real-world scenarios. The contribution of this paper is two-fold: first, we show that the Efficient Large-scale Stereo Matching algorithm (ELAS) by A. Geiger et al. 2010 for computation of the disparity map is well suited to be used on a humanoid robotic platform as the iCub robot; second, we show how, provided with a fast and reliable stereo system, implementing relatively challenging visual behaviors in natural settings can require much less effort. As a case of study we consider the common situation where the robot is asked to focus the attention on one object close in the scene, showing how a simple but effective disparity-based segmentation solves the problem in this case. Indeed this example paves the way to a variety of other similar applications

3-D Hand Pose Estimation from Kinect's Point Cloud Using Appearance Matching

We present a novel appearance-based approach for pose estimation of a human hand using the point clouds provided by the low-cost Microsoft Kinect sensor. Both the free-hand case, in which the hand is isolated from the surrounding environment, and the hand-object case, in which the different types of interactions are classified, have been considered. The hand-object case is clearly the most challenging task having to deal with multiple tracks. The approach proposed here belongs to the class of partial pose estimation where the estimated pose in a frame is used for the initialization of the next one. The pose estimation is obtained by applying a modified version of the Iterative Closest Point (ICP) algorithm to synthetic models to obtain the rigid transformation that aligns each model with respect to the input data. The proposed framework uses a "pure" point cloud as provided by the Kinect sensor without any other information such as RGB values or normal vector components. For this reason, the proposed method can also be applied to data obtained from other types of depth sensor, or RGB-D camera

Webcam based maker tracking application

Touchless technology is still considered a new field in information technology due to its effectiveness in real world application.This technology started in development in the late 80s.Although this technology has been around for about 20 years,the application of this technology is not widely.This is primarily because it is only suitable for interaction between human and computer for entertainment purposes.The example we can see is the implementation of this technology is in Xbox 360 or Microsoft Kinect, which is mainly targeted in entertainment.In order to implement this technology besides for entertainment, Webcam-based Marker Tracking Application has been developed to show its usage in writing recognition.It offers an interactive and fun way of handwriting,recognition by using marker tracking.In addition,the low cost hardware and software requirement of this technology makes it can used by anyone.Object-oriented analysis and design method has been used in the development of this project.The way this method decompose each function into object makes it easy for problem solving.This is because we can focus on the solution on one object before continues to the next.Finally,I deeply believes Touchiess can be implemented in other field besides than entertainment,probably it can be implemented in education for children learning purposes