30-01-2013, 10:14 AM
FINGER TRACKING IN REAL-TIME HUMAN COMPUTER INTERACTION
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ABSTRACT:
For a long time research on human-computer interaction (HCI) has been restricted to techniques based on the use of monitor, keyboard and mouse. Recently this paradigm has changed. Techniques such as vision, sound, speech recognition, projective displays and location aware devices allow for a much richer, multi-modal interaction between man and machine.
Finger-tracking is usage of bare hand to operate a computer in order to make human-computer interaction much more faster and easier.
Fingertip finding deals with extraction of information from hand features and positions. In this method we use the position and direction of the fingers in order to get the required segmented region of interest.
INTRODUCTION:
Finger pointing systems aim to replace pointing and clicking
devices like the mouse with the bare hand. These applications require
a robust localization of the fingertip plus the recognition of a limited
number of hand postures for “clicking-commands”.
Finger-tracking systems are considered as specialized type of hand
posture/gesture recognition system.
The typical Specializations are:
1) Only the most simple hand postures and recognized.
2) The hand usually covers a part of the on screen.
3) The finger positions are being found in real-time
4) Ideally, the system works with all kinds of backgrounds
5) The system does not restrict the speed of hand movements
In finger –tracking systems except that the real-time constraints currently do not allow sophisticated approaches such as 3D-model matching or Gabor wavelets.
METHOD:
Color Tracking Systems:
Queck build a system called “FingerMouse”, which allows control of
the mouse pointer with the fingertip ([Queck 95]). To perform a
mouse-click the user has to press the shift key on the keyboard.
Queck argues that 42% of the mouse-selection-time is actually used
to move the hand from the keyboard to the mouse and back. Most of
this time can be saved with the FingerMouse system. The tracking
works at about 15Hz and uses color look-up tables to segment the
finger (see Figure 1). The pointing posture and the fingertip
position are found by applying some simple heuristics on the line
sums of the segmented image.
Correlation Tracking Systems
Correlation yields good tracking results, as
long as the background is relatively uniform and the tracked object
moves slowly.
Correlation works performs well with slow movements; but it can only search a small part of the image and therefore fails if the finger is moving too fast.
Crowley and Bérard used correlation tracking to build a system
called “FingerPaint,” which allows the user to “paint” on the wall
with the bare finger ([Crowley 95]). The system tracks the finger
position in real-time and redisplays it with a projector to the wall (see
Figure 2.a). Moving the finger into a trigger region initializes the
correlation. Mouse down detection was simulated using the space bar
of the keyboard.
Contour-Based Tracking Systems
Contour-based finger trackers are described in [Heap 95], [Hall 99]
and [MacCormick 00]. The work of MacCormick and Blake seems
to be the most advanced in this field. The presented tracker works
reliably in real-time over cluttered background with relatively fast
hand motions. Similar to the DrawBoard application from [Laptev
00], the tracked finger position is used to paint on the screen.
Extending the thumb from the hand generates mouse clicks and the
angle of the forefinger relative to the hand controls the thickness of
the line stroke (see Figure 3).
Brainstorm:
The BrainStorm system is built for the described scenario. During
the idea generation phase, users can type their thoughts into a
wireless keyboard and attach colors to their input. The computer
automatically distributes the user input on the screen, which is
projected onto the wall. The resulting picture on the wall resembles
the old paper-pinning technique but has the big advantage that it can
be saved at any time.
For the second phase of the process, the finger-tracking system
comes into action. To rearrange the items on the wall the participants
just walk up to the wall and move the text lines around with the
finger. Figure 6.2b-d show the arranging process. First an item is
selected by placing a finger next to it for a second. The user is
notified about the selection with a sound and a color change.
Selected items can be moved freely on the screen. To let go of an
item the user has to stretch out the outer fingers as shown in figure 6.2d.
Conclusions
Finger-tracking system with the following properties:
•The system works on light background with small amounts of
clutter.
•The maximum size of the search area is about 1.5 x 1m but can
easily be increased with additional processing power.
•The system works with different light situations and adapts
automatically to changing conditions.
•No set-up stage is necessary. The user can just walk up to the
system and use it at any time.
• There are no restrictions on the speed of finger movements.
•No special hardware, markers or gloves are necessary.
•The system works at latencies of around 50ms, thus allowing
real-time interaction