Proposal 1

Projected Interactive Display for Public Spaces --------------------

A Thesis Proposal Presented to the Faculty of the Department of Electronics and Communications Engineering College of Engineering, De La Salle University

--------------------

In Partial Fulfillment of The Requirements for the Degree of Bachelor of Science in Electronics and Communications Engineering

--------------------

by Arcellana, Anthony A. Ching, Warren S. Guevara, Ram Christopher M. Santos, Marvin S. So, Jonathan N. June 2006

1. Introduction 1.1.Background of the Study Human-computer interaction (HCI) is the study of the interaction between the users and the computers. The basic goal of HCI is to improve the interaction between users and computers by making the computers more user-friendly and accessible to users. HCI in the large is an interdisciplinary area. It is emerging as a specialty concern within several disciplines, each with different emphases: computer science, psychology, sociology and industrial design (Hewett et. al., 1996). The ultimate goal of HCI is to design systems that would minimize the barrier between the human’s cognitive model of what they want to accomplish and the computer’s understanding of the user’s task. The thesis applies a new way to interact with sources of information using an interactive projected display. For a long time the ubiquitous mouse and keyboard has been used to control a graphical display. With the advent of increased processing power and technology, there has been great interest from the academic and commercial sector in developing new and innovative human computer interfaces in the past decades. (Myers et. al., 1996). Recently advances and research in human computer interaction (HCI) has paved the way for techniques such as vision, sound, speech recognition, and context-aware devices that allow for a much richer, multimodal interaction between man and machine. (Turk, 1998; Porta, 2002). This type of recent research moves away from traditional input devices which are essentially blind into the so called Perceptual User Interfaces (PUI). PUI are interfaces that emulate the natural capabilities of humans to sense, perceive, and

reason. It models human-computer interaction after human-human interaction. Some of the advantages of PUIs are as follows: (1) it reduces the dependence on being in proximity that is required by keyboards and mouse systems, (2) it makes use of communication techniques found natural in humans, making the interface easy to use,(3) it allows interfaces to be built for a wider range of users and tasks, (4) it creates interfaces that are user-centered and not device centered, and (5) it has design emphasis on being a transparent and unobtrusive interface. (Turk, 1998). What is interesting in this line of research is the development of natural and intuitive interface methods that make use of body language. A subset of PUI is Vision Based Interfaces (VBI) which focuses on the visual awareness of computers to the people using them. Here computer vision algorithms are used to locate and identify individuals, track human body motions, model the head, and face, track facial features, interpret human motion and actions. (Porta, 2002) A certain class of this research falls under bare hand human-computer interaction which this study is about. Bare hand human interaction uses as a basis of input, the actions and gestures of the human hands alone without the use of attached devices.

1.2.Statement of the Problem Information-rich interactive viewing modules are usually implemented as computer based kiosks. However placing computer peripherals such as touch-screens and mouse and keyboard controlled computers in a public area would require significant space and have maintenance concerns on the physical hardware being used by the common public. Using a projected display and a camera based input device,

would eliminate the hardware problems associated with the space and maintenance. It also attracts people since projected displays are new and novel.

1.3.Objectives 1.3.1.General Objectives The general objective of the thesis is to create an interactive projected display system using a projector and a camera. The projector would display the interactive content and the user would use his hand to select objects in the projected display. Computer vision is used to detect and track the hand and generate the proper response. 1.3.2.Specific Objectives 1.3.2.1. To use a DLP or LCD projector for the display 1.3.2.2. To use a PC camera as the basis of user input 1.3.2.3. To use a PC to implement algorithms to detect hand action as seen from the camera 1.3.2.4. To use a PC to host the information-rich content 1.3.2.5. To create an interactive DLSU campus map as a demo application

1.4.Scope and Delimitation 1.4.1.Scope of the Study 1.4.1.1. The proponents will create a real time interactive projected display using a projector and camera. 1.4.1.2. The proponents will use development tools for image/video processing and computer vision to program the PC. Algorithms for hand detection and tracking will be implemented using these tools.

1.4.1.3. A demo application of the system will be implemented as an interactive campus map of the school. 1.4.1.4. Only the posture of a pointing hand will be recognize as an input. Other visual cues to the camera will not be recognized. 1.4.2.Delimitation of the Study 1.4.2.1. The display will be projected in a clean white wall. 1.4.2.2. The projector and the camera set-up will be fixed in such a way that blocking the projector is not a problem. 1.4.2.3. Trapezoidal distortion which results from projecting from an angle will be manually compensated if present. 1.4.2.4. Lighting conditions will be controlled to not overpower the projector. 1.4.2.5. The system will be designed to handle only a single user. In the presence of multiple users, the system would respond to the first user triggering an event.

1.5.Significance of the Study The study applies a new way of presenting information using projected displays and allows the user to interact with it. A projected display conserves space as the system is ceiling mounted and there is no hardware that directly involves the user. Using only the hands of the user as an input, the system is intuitive and natural-- key criteria for effective interfaces. It presents an alternative to computer based modules where space can be a problem.

Currently there is a high cost of acquiring and maintaining a projector. But it is still viable when maintaining an information center is deemed to be important. The system can be comparable to large screen displays that are used in malls and such. Since the system is also a novel way of presenting information. It can be used to make interactive advertisements that are very attracting to consumers. The display can transform from an inviting advertisement into detailed product information. With this said, the cost of the operation of the projector can possibly be justified with the revenue generated from effective advertising. The study is an endeavor towards the development of natural interfaces. The use of a projector and camera provides a means of producing an augmented reality that is natural-- requiring no special goggles or gloves that the user has to wear. In public spaces where information is very valuable, a system that can provide an added dimension to reality is very advantageous and the use of nothing but the hands means the user can instantly tap the content of the projected interface. Computer vision provides the implementation of a perceptual user interface and the projection provide the means of creating an augmented reality. Further developments in these areas means the presence of computers can be present in everyday life without being perceived as such. With PUI there is no need for physical interface hardware, only the use of natural interaction skills present in every human is needed.

1.6.Description of the Project The system is comprised of 3 main components; (1) the PC which houses the information and control content, (2) the projector which displays the information, and (3) the PC camera which is the input of the system. Development of the study would

be heavily invested in the software programming of the PC. The functions of the PC would be the following: detection of the position and action of the hands of the user relative to the screen, generating a response from a specific action, hosting the information rich content. Techniques of image/video processing and machine vision will be used to facilitate the first two functions of the PC. As a demo application an interactive map of the school is used. The projector will project the campus directory of De La Salle University Manila. The camera will capture the images needed and will upload to the computer. The user will then pick on which building he/she would like to explore using his/her hand as the pointing tool. Once the user has chosen a building, a menu will appear that will give information about the building. Information includes brief history, floor plans, facilities, faculties, etc. Once the user is finished exploring the building, he/she can touch the back button to select another building in the campus. The cycle will just continue until the user is satisfied.

1.7.Methodology Development of the study would be heavily invested in the software programming of the PC. We the researchers must spend time in acquiring skills in programming for the implementation of the research. Research about video capture and processing is greatly needed for the operation of the system. Quick familiarization and efficiency with the libraries and tools for computer vision is necessary for timely progress in the study.

The proponents of the research must first obtain the hardware that is needed for the achievement of the study, materials such as the camera that will capture the input, the projector which will give the output display (projected display) and the PC which the system will be based. The appropriate specifications of the camera and the projector will be carefully looked at to get the precise requirements. After which the system has its working prototype, testing and making the necessary adjustments will be needed upon detecting and fixing problems in the system. Seeking advice from different people may be necessary for speedy progress of the study. Advice in programming will be very helpful, since the implementation is PC based. Additionally advice from the panel, adviser, and other people about the interface will be helpful in removing biases the proponents may have in the system.

1.8.Gantt Chart

1.9.Estimated Cost Projector PC Camera

P 50,000 P 1500-2000

Open Source SDK

Free

Development / Prototype Computer Available Miscellaneous Estimated budget

P5000 P 57000

2. Review of Related Literature 2.1.PC Camera PC Camera, popularly known as web camera or webcam, is a real time camera widely used for video conferencing via the Internet. Acquired images from this device were uploaded in a web server hence making it accessible using the world wide web, instant messaging, or a PC video calling application. Over the years, several applications were developed including in the field of astrophotography, traffic monitoring, and weather monitoring. Web cameras typically includes a lens, an image sensor, and some support electronics. Image sensors can be a CMOS or CCD, the former being the dominant for low-cost cameras. Typically, consumer webcams offers a resolution in the VGA region having a rate of around 25 frames per second. Various lens were also available, the most being a plastic lens that can be screwed in and out to manually control the camera focus. Support electronics is present to read the image from the sensor and transmit it to the host computer (Wikipedia).

2.2.Projectors Projectors are classified into two technologies, DLP (Digital Light Processing) and LCD (Liquid Crystal Display). This refers to the internal mechanisms that the projector uses to compose the image (Projectorpoint). 2.2.1.DLP DLP technology uses an optical semiconductor known as the Digital Micromirror Device, or DMD chip to recreate the source material. Below is an illustration of how it works (Projectorpoint).

2.2.1.1. Advantages of DLP projectors There are advantages of DLP projectors over the LCD projectors. First, there is less ‘chicken wire’ or ‘screen door’ effect on DLP because pixels in DLP are much closer together. Another advantage is that it has higher contrast compared to LCD. DLP projectors are much portable for it only requires fewer components and finally, claims had shown that DLP projectors last longer than LCD (Projectorpoint). 2.2.1.2. Disadvantages of DLP projectors Certainly, DLP projectors also have disadvantages to consider. It has less color saturation. The ‘rainbow effect’ is appearing when looking from one side of the screen to the other, or when looking away from the projected image to an off-screen object and sometimes ‘Halo effect’ appears (Projectorpoint). 2.2.2.LCD LCD projectors contain three separate LCD glass panels, one for red, green, and blue components of the image signal being transferred to the projector. As the light passes through the LCD panels, individual pixels can be opened to allow light to pass or closed to block the light. This activity modulates the light and produces the image that is projected onto the screen (Projectorpoint). 2.2.2.1. Advantages of LCD projectors Advantages of LCD projectors over the DLP projectors include: It is more ‘light efficient’ than DLP. It produces more saturated colors making it seem brighter than a DLP projector. It produces sharper image (Projectorpoint).

2.2.2.2. Disadvantages of LCD projectors Disadvantages of LCD projectors over DLP projectors are: It produces ‘chicken wire’ effect causing the image to look more pixellated. LCD projectors are more bulky because there are more internal components. Dead pixels, which are pixels that are permanently on or permanently off, appear which can be irritating to see. LCD panels can fail, and are very expensive to replace (Projectorpoint).

2.3.Similar Researches 2.3.1.Bare-Hand Human –Computer Interface Human-computer interaction describes the interaction between the user and the machine. Devices such as keyboard, mouse, joystick, electronic pens and remote controls were commonly used as the means for human-computer interaction. Real-time barehanded interaction is the controlling of computer system without any device or wires attached to the user. The position of the fingers and the hand is to be used to control the applications (Hardenburg, 2001). 2.3.1.1. Applications Bare-hand computer interaction is more practical than traditional input devices. A good example is during a presentation, the presenter may use hand gestures for selecting slides therefore minimizing the delay or pauses caused by moving back and fourth to the computer system to click for the slide. Perceptual interface allows systems to be integrated in small areas and allows users to operate at a certain distance. Direct manipulation of virtual objects using fingers is made possible with this system. Also, with this system,

indestructible interface could be built by mounting the projector and camera high enough for the user not to access or touch it. With these, the system will be less prone to damage caused by the users (Hardenburg, 2001). 2.3.1.2. Functional Requirements Functional requirement includes the services for a vision-based computer interaction system. The three essential services needed in the implementation of the aforementioned system are detection, identification and tracking. Detection determines the presence and position of the objects acquired. The output of detection could be used for controlling applications. Identification service recognizes if the object present in the scene is within the given class of objects. Some of the identification tasks were the identification of certain hand posture and number of fingers visible. Tracking service is required to be able to tell which object moved between two frames since the identified objects will not rest in the same position over the time (Hardenburg, 2001). 2.3.1.3. Non-Functional Requirements Non-functional requirements describe the minimum quality expected from a service. The qualities to be monitored and maintained are latency, resolution and stability. Latency is defined as the lag between the user’s action and the response of the system. Eventually there is no system without latency therefore the acceptable latency of the system is of given importance since the application requires real-time interaction. Minimum input resolution is important in the detection and identification processes. It is difficult to

identify fingers with a resolution width below six pixels. Tracking service is said to be stable as long as the tracking object does not move and as long as the measured position does not change (Hardenburg, 2001). 2.3.2.Dynamically Reconfigurable Vision-Based User Interfaces Vision-based user interfaces (VB-UI) are an emerging area of user interface technology where a user’s intentional gestures are detected via camera, interpreted and used to control an application. The paper describes a system where the application sends the vision system a description of the user interface as a configuration of widgets. Based on this, the vision system assembles a set of image processing components that implement the interface, sharing computational resources when possible. The parameters of the surfaces where the interface can be realized are defined and stored independently of any particular interface. These include the size, location and perspective distortion within the image and characteristics of the physical environment around that surface, such as the user’s likely position while interacting with it. The framework presented in this paper should be seen as a way that vision based applications can easily adapt to different environments. Moreover, the proposed vision-system architecture is very appropriate for the increasingly common situations where the interface surface is not static (Kjeldsen, 2003.). 2.3.2.1. Basic Elements A VB-UI is composed of configurations, widgets, and surfaces. Configurations are a set of individual interaction dialogs. It specifies a boundary area that defines the configuration coordinate system. The boundary

is used during the process of mapping a configuration onto a particular surface. Each configuration is a collection of interactive widgets. A widget provides an elemental user interaction, such as detecting a touch or tracking a fingertip. It generates events back to the controlling application where they are mapped to control actions such as triggering an event or establishing a value of a parameter. A surface is essentially the camera’s view of a plane in 3D space. It is able to define the spatial layout of widgets with respect to each other and the world but it should not be concerned with the details of the recognition process (Kjeldsen, 2003). 2.3.2.2. Architecture In this system, each widget is represented internally as a tree of components. Each component performs one step in the widget’s operation. There are components for finding the moving pixels in an image (Motion Detection), finding and tracking fingertips in the motion data (Fingertip Tracking), looking for touch-like motions in the fingertip paths (Touch Motion Detection), generating the touch event for the application (Event Generation), storing the region of application space where this widget resides (Image Region Definition), and managing the transformation between application space and the image (Surface Transformation) (Kjeldsen, 2003).

The figure below shows the component tree of a “touch button” and the “tracking area.”

2.3.2.3. Example Applications One experimental application developed that used the dynamically reconfigurable vision system is the Everywhere Display Projector (ED). This provides information access in retail spaces. The Product Finder Application is another example. Its goal is to allow customer to look up products in a store directory, and then guide him/her to where the product is (Kjeldsen, 2003.). 2.3.3.Computer Vision-Based Gesture Recognition for an Augmented Reality Interface Current researchers are discerning the realization of taking out computers in other places than in our desktops while eyeing everywhere computation as one of their objectives. The idea of wearable computers to enhance human visual sensors by augmenting image generated information on a visual input is one of

these issues. One of the main proponents of the research is Gesture-Recognition as the input such as pointing and clicking of a finger. It has been classified that gesture recognition has two steps: 1.) capturing the motion of the user input and 2.) Classify the gesture to its predefined gesture classes. Capturing is either performed by glove–based or optical-based system. Optical-based gesture recognition comprise of model-based and appearance-based category. In a modelbased system a geometric model of the hand is created where it is matched to the image data to define the state of the hand. While in appearance-based system the recognition is based on a pixel representation learned from training images. Because both approaches require a lot of computational complexity which is not desirable for Augmented Reality (AR) systems it requires enhancements like markers and infrared lightings. Gesture recognition will be introduced and the main topic in this paper in order to make useful interface, as well as having a low computational complexity. Outline of the paper will be done to show how the research is implemented (Moeslund T., 2004). 2.3.3.1. Defining the Gestures Two primary gestures are introduced, pointing and clicking gesture of the hand. Consideration of minimum requirements to control the application is done also it include other easy to remember gestures that will help in short-cut commands to be able to avoid numerous pop-up menus (Moeslund T., 2004).

2.3.3.2. Segmentation Task of the segmentation will be for the recognition and detection of the placeholder objects and pointers where the visual output of the system will be projected as well as hands in the 2d image captured. In order to achieve invariance to changing size and form of objects to be detected the research used colour pixel-based approach to segment spots of similar colour image. Problems like lighting settings, changing illumination and skin colour detection is discussed and was given solutions to (Moeslund T., 2004). 2.3.3.3. Gesture Recognition A basic approach is done to solve this problem, by counting the number of fingers. Hand and fingers can be approximated by a circle and a number of rectangles, where it equates to the number of the finger that is projected. Polar transformation around the centre of the hand and count the number of fingers (rectangles) present in each radius. The algorithm does not contain any information regarding the relative distances between two fingers, because it makes the system more general, and secondly because different users tend to have different preferences in the shape and size of their hands (Moeslund T., 2004).

2.3.3.4. System Performance Gesture-recognition has been implemented as part of the computer vision system of a computer vision system of an AR multi-user application. The low level segmentation (section 3) can robustly segment 7 different colours from the background (skin colour and 6 colours for PHO and pointers), given there are no big changes in the illumination colour (Moeslund T., 2004).

Segmentation Result 2.3.4.A Design Tool for Camera-Based Interaction Constructing a camera-based interface can be difficult for most programmers and would require a better understanding of machine algorithms that are involve. Basically a camera-based interface is that a camera will serve as the sensor/eyes of the system regarding with your input. The goal is to make the system interactive while not wearing any other special devices to detect the input rather than having other traditional inputs like keyboard etc. This makes computing set in the environment rather than in our desktops. Problem lies in the designing of a camera-based system, the programming and the mathematics part

is complicated that ordinary programmers do not have the skill for it especially when we are considering bare-hand inputs. The main item to be considered in a camera-based interaction is a classifier that takes an image and identifies pixels that is considered. Acquiring skills in building a classifier is greatly needed to pursue the idea (Fails, J.A., 2003). Crayons is one of the tools to make a classifier which can be exported in a form that can be read by java. Crayons help User Interface (UI) designers to make the camera-based interface even without detailed knowledge on image processing. But its features are unable to distinguish shapes and object orientation but do well in object-detection and hand and object tracking (Fails, J.A., 2003).

Classifier Design Process The function of the Crayons is to create a classifier with ease. Crayons receive images and then after the user gives its input a classifier is created then a feedback is displayed (Fails, J.A., 2003). 2.3.4.1. User Interfaces There are four pieces of information that a designer must consider and operate in designing a classifier interface which are: 1.) set of classes to be recognized, 2.) Set of training images to be used, 3.) classification of pixels as defined by the programmer and 4.) the classifier’s current classification of the pixels (Fails, J.A., 2003). 2.3.4.2. Crayons Classifier

Automating the classifier creation is the main function of the crayon tool. It is required to extract features and generate classifiers as quickly as possible. Current Crayons prototype has about 175 features per pixel (Fails, J.A., 2003). Lastly to accomplish the application a machine learning algorithm that can handle a large number of examples with a large number of features is required (Fails, J.A., 2003). 2.3.5.Using Marking Menus to Develop Command Sets for Computer Vision Based Hand Gesture Interfaces The use of hand gestures for interaction, in an approach based on computer vision. The purpose is to study if marking menus, with practice, could support the development of autonomous command sets for gestural interaction. Some early problems are reported, mainly concerning with user fatigue and precision of gestures (Lenman, S., 2002). Remote control of electronic appliances in a home environment, such as TV sets and DVD players, has been chosen as a starting point. Normally it requires the use of a number of devices, and there are clear benefits to an appliance-free approach. They only implemented a first prototype for exploring pie- and marking menus for gesture-based interaction (Lenman, S., 2002). 2.3.5.1. Perceptive and Multimodal User Interfaces Perceptive User Interfaces (PUI) strives for automatic recognition of natural, human gestures integrated with other human expressions, such as body movements, gaze, facial expression, and speech. The second approach to

gestural interfaces will be the Multimodal User Interfaces (MUI), where hand poses and specific gestures are used as commands in a command language. In this approach, gestures are either a replacement for other interaction tools, such as remote controls, mouse, or other interaction devices. The gestures need not be natural gestures but could be developed for the situation, or based on a standard sign language. There is a growing interest in designing multimodal interfaces that incorporate vision-based technologies. It contrasts the passive mode of PUI with the active input mode addressed here. It claims that although passive modes may be less obtrusive, active modes generally are more reliable indicators of user intent, and not as prone to error. The design space for such commands can be characterized along three dimensions: Cognitive aspects, Articulatory aspects, and Technological aspects. Cognitive aspects refer to how easy commands are to learn and to remember. It is often claimed that gestural command sets should be natural and intuitive, meaning that they should inherently make sense to the user. Articulatory aspects refer to how easy gestures are to perform, and how tiring they are for the user. Gestures involving complicated hand or finger poses should be avoided, because they are difficult to articulate. Technological aspects refer to the fact that in order to be appropriate for practical use, and not only in visionary scenarios and controlled laboratory

situations, a command set for gestural interaction based on computer vision must take into account the state-of-the art of technology (Lenman, S., 2002). 2.3.5.2. Current Work The point of departure for the current work is cognitive, leaving articulatory aspects aside at the moment. A command language based on a menu structure has the cognitive advantage that the commands can be recognized rather than recalled. Traditional menu based interaction is not attractive in a gesture-based scenario. Pie- and marking menus might provide a foundation for developing directness and autonomous gestural command sets (Lenman, S., 2002). Pie menus are pop-up menus with the alternatives arranged radially. Because the gesture to select an item is directional, users can learn to make selections without looking at the menu. The direction of the gesture is sufficient to recognize the selection. If the user hesitates at some point in the interaction, the underlying menus can be popped up, always giving the opportunity to get feedback about the current selection. Hierarchic marking menus are a development of pie menus that allow more complex choices by the use of sub-menus. The shape of the gesture (mark) with its movements and turns can be recognized as a selection, instead of the sequence of distinct choices between alternatives. The gestures in the command set would consist of a start pose, a trajectory defined by menu organization for each possible selection and, lastly

a selection pose. Gestures ending in any other way than with the selection pose would be discarded (Lenman, S., 2002). 2.3.5.3. A Prototype for Hand Gesture Interaction Here remote control appliances in a domestic environment were chosen as the first application. So far, the only designed hierarchic menu system is for controlling some functions of a TV, a CD player, and a lamp (Lenman, S., 2002). The hand was chosen as a view-based representation which includes both color and shape cues. The system tracks and recognizes the hand poses based on a combination of multi-scale color feature detection, view-based hierarchical hand models and particle filtering. The hand poses are represented in terms of hierarchies of color image features at different scales, with qualitative interrelations in terms of scale, position and orientation. These hierarchical models capture the coarse shape of the hand poses. In each image, detection of multi-scale color features is performed. The particle filtering allows for the evaluation of multiple hypotheses about the hand position, state, orientation and scale, and a possibility measure determines what hypothesis to choose. To improve the performance of the system, a prior on skin color is included in the particle filtering step. In fig. 1, yellow (white) ellipses show detected multi-scale features in a complex scene and the correctly detected and recognized hand pose is superimposed in red (gray).

Detected multi-scale features and the recognized hand pose superimposed in an image of a complex scene There is a large number of works on real-time hand pose recognition in the computer vision literature. Some of the most related in this approach is by using normalized correlation of template images of hands for hand pose recognition. Though efficient, this technique can be expected to be more sensitive to different users, deformations of the pose and changes in view, scale, and background. However, the performance was far from real-time. The approach closest was representing the poses as elastic graphs with local jets of Gabor filters computed at each vertex. In order to maximize speed and accuracy in the prototype, gesture recognition is currently tuned to work against a uniform background within a limited area, approximately 0.5 by 0,65m in size, at a distance of approximately 3m from the camera, and under relatively fixed lighting conditions (Lenman, S., 2002).

The demo space at CID

2.4.Similar Product An Interactive Whiteboard (IW) is a projector-screen, except that the screen is either touch sensitive or can respond to a special ‘pen.’ This means that the projectorscreen can be used to interact with the projected user image. This provides a more intuitive way to interact rather than using input devices such as the mouse/keyboard for navigation of the computer screen being projected. There are two basic functions of an IW, writing on the board and acting as a mouse. All common IWs have character-recognition and can convert scrawls into text-boxes. There are two market leaders in IWs. They are Promethean ActivBoard and SmartBoard. Promethean has its own presentation system, web browser, and its own file system. SmartBoard uses the computer’s native browser. Promethean uses stylus pen to interact with the board while the SmartBoard are touched to operate. The reason to prefer one to the other will depend on its applications. There are some issues regarding IWs. One of which is that it requires a computer with an IW software installed. The need for a software makes it awkward to use an IW with individual laptops. Another issue is that all IWs used were “front-lit”

meaning that the user’s shadow will be thrown across the screen. Backlit IWs currently are very expensive. Lastly, although IWs have both character-recognition and an onscreen keyboard, it is not a good technology for typing. The user can easily go back to the computer keyboard when he/she needs to do a lot of typing. (Stowell, 2003)

2.5.Computer Vision and Image Processing Development Tools 2.5.1.Open CV OpenCV which stands for Open Computer Vision is an open source library developed by Intel. This library is cross-platform which runs both on Windows and Linux and mainly focuses on real-time image processing. This library is intended for use, incorporation and modification by researchers, commercial software developers, government and camera vendors as reflected in the license (Open Source Computer Vision Library). 2.5.2.Microsoft Vision SDK Microsoft Vision SDK is a library for writing programs to perform manipulation and analysis on computers running on Microsoft Windows operating systems. The library was developed to support researchers and developers of advanced applications, including real-time image processing applications. Microsoft Vision SDK is a C++ library of object definitions, related software, and documentation for use with Microsoft Visual C++. It is a low-level binary, intended to provide a strong programming foundation for research and application development. It includes classes and functions for working with images but it does not include image processing predefined functions (Intel, n.d.).

References: DLP and LCD Projector Technology Explained. (n.d.). Retrieved June 2, 2006, from http://www.projectorpoint.co.uk/projectorLCDvsDLP.htm. Fails, J.A., Olsen, D. (2003). A Design Tool for Camera-Based Interaction. Bringham University, Utah. Retrieved from http://icie.cs.byu.edu/Papers/CameraBaseInteraction.pdf Hardenberg, C., Bérard, F., (2001). Bare-hand human-computer interaction. Orlando, FL USA. Retrieved from Hewett, et. al. (1996) Chapter 2: Human Computer Interaction. ACM SIGCHI Curricila for Human Computer Interaction. Available: http://sigchi.org/cdg/cdg2.html#2_3 retrieved June 2, 2006. Intel, (n.d.). Open source computer vision library. Retrieved June 4, 2006 from http://www.intel.com/technology/computing/opencv/index.htm. Kjeldsen, R., Levas, A., & Pinhanez, C. (2003). Dynamically Reconfigurable VisionBased User Interface. Retrieved from http://www.research.ibm.com/ed/publications/icvs03.pdf Lenman, S., Bretzner, L., Thuresson B., (2002, October). Using Marking Menus to Develop Command Sets for Computer Vision Based Hand Gesture Interfaces. Retrieved from http://delivery.acm.org/10.1145/580000/572055/p239lenman.pdf?key1=572055&key2=1405429411&coll=GUIDE&dl=ACM&CFID= 77345099&CFTOKEN=54215790 Moeslund T., Liu Y., Storring M., (2004, September). Computer Vision-Based Gesture Recognition for an Augmented Reality Interface. Marbella, Spain. Retrieved from http://www.cs.sfu.ca/~mori/courses/cmpt882/papers/augreality.pdf Myers B., et. al. (1996) Strategic Directions in Human-Computer Interaction. ACM Computing Surveys Vol.28 No.4 Porta, M. (2002) Vision-based user interfaces:methods and applications. International Journal of Human Computer Studies. Elsevier Science Stowell, D. (May, 2003). Interactive Witeboard. Retrieved June 1, 2006 from http://www.ucl.ac.uk/is/fiso/lifesciences/whiteboard. The

Microsoft Vision SDK. (2000, May). Retrieved http://robotics.dem.uc.pt/norberto/nicola/visSdk.pdf

June

4,

2006

from

Turk, M. (1998). Moving from GUIs to PUIs. Symposium on Intelligent Information Media. Microsoft Research Technical Report MSR-TR-98-69 Webcam. (n.d.). Wikipedia. Retrieved June 03, 2006, from Answers.com Web site: http://www.answers.com/topic/web-cam.