When people share a workspace, they naturally create visual structures which organize resources, communicate interpretations, and coordinate activities. To support this mode of communication and coordination we have built the Visual Knowledge Builder (VKB.) VKB supports the incremental visual interpretation of information. Through the emergence and evolution of visual languages, communication between VKB users sharing a workspace grows over time. VKB has been used for two years in note taking, writing, curriculum development, project management, and conference organization. These tasks include short-and long-term synchronous and asynchronous activities. Features such as the recognition of implicit spatial structure and navigable history facilitate the authoring and comprehension of shared visual information spaces. VKB has also been used in a more controlled setting by pairs of people writing a poem with a constrained vocabulary. This use of VKB has been compared to the same task using Magnetic Poetry sets to better understand how the characteristics of the tools and information space impact collaborative practice.
When people share a workspace, they naturally create visual structures which organize resources, communicate interpretations, and coordinate activities. To support this mode of communication and coordination we have built the Visual Knowledge Builder (VKB.) VKB supports the incremental visual interpretation of information. Through the emergence and evolution of visual languages, communication between VKB users sharing a workspace grows over time. VKB has been used for two years in note taking, writing, curriculum development, project management, and conference organization. These tasks include short-and long-term synchronous and asynchronous activities. Features such as the recognition of implicit spatial structure and navigable history facilitate the authoring and comprehension of shared visual information spaces. VKB has also been used in a more controlled setting by pairs of people writing a poem with a constrained vocabulary. This use of VKB has been compared to the same task using Magnetic Poetry sets to better understand how the characteristics of the tools and information space impact collaborative practice.
N-UU class mechanisms, exemplified by the Omni-Wrist III, are compact parallel kinematic mechanisms (PKM) with large singularity free workspaces. These characteristics make them ideal for applications in robot wrists. This article presents the detailed kinematic and workspace analysis for four N-UU class mechanisms. More in detail, the equations defining the mechanism’s moving platform kinematics are derived as a function of the motion of the input links; these are then used to explore the mechanism’s workspace. These results are furthermore validated by comparing them to the results obtained from CAD-based simulations. The analyses suggests that the workspace of the mechanism is non-uniform, with a “warping” behaviour that occurs in an asymmetric fashion in a specific region of the workspace. Furthermore we show how the rotation of the input links, which mainly actuates the yaw and pitch angles of the mechanism, also causes unwanted coupled rotations along the roll axis.
Bimanual gestures are of the utmost importance for the study of motor coordination in humans and in everyday activities. A reliable detection of bimanual gestures in unconstrained environments is fundamental for their clinical study and to assess common activities of daily living. This paper investigates techniques for a reliable, unconstrained detection and classification of bimanual gestures. It assumes the availability of inertial data originating from the two hands/arms, builds upon a previously developed technique for gesture modelling based on Gaussian Mixture Modelling (GMM) and Gaussian Mixture Regression (GMR), and compares different modelling and classification techniques, which are based on a number of assumptions inspired by literature about how bimanual gestures are represented and modelled in the brain. Experiments show results related to 5 everyday bimanual activities, which have been selected on the basis of three main parameters: (not) constraining the two hands by a physical tool, (not) requiring a specific sequence of single-hand gestures, being recursive (or not). In the best performing combination of modelling approach and classification technique, five out of five activities are recognised up to an accuracy of 97%, a precision of 82% and a level of recall of 100%.
The main objective of this paper is to propose a SIMULINK MODEL to detect moving vehicles. Background subtraction is the technique used in this algorithm. Based on the retrieved information, automatic traffic surveillance can be done. Initially, a recorded video is given directly to the blocks. The main logic is then implemented using various Embedded MATLAB blocks using individual algorithms. The algorithm takes into consideration three main techniques namely Background Subtraction, Edge Detection and Shadow Detection. Background Subtraction block is sub-divided into Selective and Non-selective parts to improve the sensitivity and give accurate background. Edge detection helps to detect the exact boundaries of moving vehicles. This is followed by the shadow detection block that removes the falsely detected pixels that are generated due to shadow of the vehicle. By analyzing the output of the blocks discussed above, the final mask is generated. The mask along with the input frame processed to give the final video output with the detected object. Furthermore, using a Blob analysis block, parameters such as number of blobs per frame (vehicles) and the area of blobs can be used directly for traffic surveillance. Finally a Blob counting block is used to count and display the total number of cars.
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