Mouse Simulation Using Two Coloured Tapes

In this paper, we present a novel approach for Human Computer Interaction (HCI) where, we control cursor movement using a real-time camera. Current methods involve changing mouse parts such as adding more buttons or changing the position of the tracking ball. Instead, our method is to use a camera and computer vision technology, such as image segmentation and gesture recognition, to control mouse tasks (left and right clicking, double-clicking, and scrolling) and we show how it can perform everything as current mouse devices can. The software will be developed in JAVA language. Recognition and pose estimation in this system are user independent and robust as we will be using colour tapes on our finger to perform actions. The software can be used as an intuitive input interface to applications that require multi-dimensional control e.g. computer games etc.Comment: 5 page

Pictures in Your Mind: Using Interactive Gesture-Controlled Reliefs to Explore Art

Tactile reliefs offer many benefits over the more classic raised line drawings or tactile diagrams, as depth, 3D shape, and surface textures are directly perceivable. Although often created for blind and visually impaired (BVI) people, a wider range of people may benefit from such multimodal material. However, some reliefs are still difficult to understand without proper guidance or accompanying verbal descriptions, hindering autonomous exploration. In this work, we present a gesture-controlled interactive audio guide (IAG) based on recent low-cost depth cameras that can be operated directly with the hands on relief surfaces during tactile exploration. The interactively explorable, location-dependent verbal and captioned descriptions promise rapid tactile accessibility to 2.5D spatial information in a home or education setting, to online resources, or as a kiosk installation at public places. We present a working prototype, discuss design decisions, and present the results of two evaluation studies: the first with 13 BVI test users and the second follow-up study with 14 test users across a wide range of people with differences and difficulties associated with perception, memory, cognition, and communication. The participant-led research method of this latter study prompted new, significant and innovative developments

3DTouch: A wearable 3D input device with an optical sensor and a 9-DOF inertial measurement unit

We present 3DTouch, a novel 3D wearable input device worn on the fingertip for 3D manipulation tasks. 3DTouch is designed to fill the missing gap of a 3D input device that is self-contained, mobile, and universally working across various 3D platforms. This paper presents a low-cost solution to designing and implementing such a device. Our approach relies on relative positioning technique using an optical laser sensor and a 9-DOF inertial measurement unit. 3DTouch is self-contained, and designed to universally work on various 3D platforms. The device employs touch input for the benefits of passive haptic feedback, and movement stability. On the other hand, with touch interaction, 3DTouch is conceptually less fatiguing to use over many hours than 3D spatial input devices. We propose a set of 3D interaction techniques including selection, translation, and rotation using 3DTouch. An evaluation also demonstrates the device's tracking accuracy of 1.10 mm and 2.33 degrees for subtle touch interaction in 3D space. Modular solutions like 3DTouch opens up a whole new design space for interaction techniques to further develop on.Comment: 8 pages, 7 figure

Multi-Modal Human-Machine Communication for Instructing Robot Grasping Tasks

A major challenge for the realization of intelligent robots is to supply them with cognitive abilities in order to allow ordinary users to program them easily and intuitively. One way of such programming is teaching work tasks by interactive demonstration. To make this effective and convenient for the user, the machine must be capable to establish a common focus of attention and be able to use and integrate spoken instructions, visual perceptions, and non-verbal clues like gestural commands. We report progress in building a hybrid architecture that combines statistical methods, neural networks, and finite state machines into an integrated system for instructing grasping tasks by man-machine interaction. The system combines the GRAVIS-robot for visual attention and gestural instruction with an intelligent interface for speech recognition and linguistic interpretation, and an modality fusion module to allow multi-modal task-oriented man-machine communication with respect to dextrous robot manipulation of objects.Comment: 7 pages, 8 figure