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RotoView Non-linear Dynamic Response (NLDR) Algorithms

The RotoView Non-linear Dynamic Response (NLDR) algorithms determine the amount of view navigation in response to the tilt and movement of the hand held device.

The NLDR algorithms exhibit two main features:

1. Non-linear relation between the amount of tilt or hand movement and the amount (or rate) of view navigation.
2. This non linear relation further changes dynamically during the navigation process.

Fig. 1 introduce the response curve as the relation between the sensor data and the view navigation rate. The response curves show the behavior per each axis, and there are generally a plurality of response curves that can be selected by the various applications. The blue curve illustrate a simple linear sensitivity while the red curve introduces some non-linear relations. First, there are two threshold points between which the view navigation is halted. This is needed to eliminate normal hand shaking. There are also clipping points to eliminate noise, particularly if special gestures are used to activate the view navigation.



         Figure 1

The response curve can also have different sensitivities, based upon the magnitude of the sensor data as shown in Fig. 2.



         Figure 2

We should note that the term "non-linear" is used loosely here to indicate that the response to the sensor data is not necessarily approximated by a single line (like the blue line in Fig. 1). In reality, the response graph is approximated by multiple short linear sections. This provides for proper filtering of too strong hand movements and setting a threshold level for the response, as illustrated by the noise clipping in the red curves of Fig. 1 and Fig.2.

Fig. 3 illustrates a simplified example of the dynamic response of the NLDR features taken along one axis only. The bottom graph (green) shows the raw sensor data over time, representing two consequent side-to-side tilts of the hand held device. The top graph (red) shows the view navigation rate by which RotoView responds to the sensor data.



         Figure 3

We can see that the navigation rate is coarse (strong) during the first tilt and it dynamically reduces to provide a fine navigation during the second side-to-side tilt.

We define the relation between the view navigation rate and the sensor data along each axis as the sensitivity. The sensitivity of both axis may be different. The graph depicting the dynamic non-linear change of the intensity versus time is called time response graph. A time response graph is normalized, so that its time axis (horizontal length) should be mapped to a desired time length. The vertical axis is the relative intensity, and is further scaled within the RotoView algorithms. Fig. 4 shows several examples of time response graphs.

Typical response start with coarse navigation followed by a fine navigation from which the navigation mode is exited.		This fixed response graph can be selected for instances were the stored virtual view is not much larger than the screen view.		This response graph emulates a "flick" gesture. start from fine navigation and creates a sharp coarse navigation before returning to fine navigation.

         Figure 4

In the first example of Fig. 4, the intensity for the first 3 time slots of navigation mode is set to 6 for initial coarse view navigation. From time slot 3 to 5 the intensity goes down to 4, thus providing fine view navigation. This graph results in the behavior of Fig. 3.


The second example of Fig. 4 show the use of a simple fixed response. This may be selected automatically (or by the user) for instances where the stored view is not much larger than the actual screen view. The last example emulates the "flick" action, particularly if the graph is mapped to a sort time length.

The NLDR algorithms create a natural subliminal closed loop comprising the user's hand movements and the resultant navigation. By eliminating the need for one-to-one mapping between a tilt or hand movement and the exact view positioning, RotoView allows for smoother and more intuitive view navigation. Users can setup the NLDR to their exact preference to achieve the most comfortable results.

The NLDR algorithms further enable the use of sensors with lower accuracy since there is no need for an exact alignment of the displayed view with the relative tilt. This may have important low cost benefits for mass production.

Additional issues relating to the user interface experience with RotoView are detailed at www.rotoview.com/rv_user_interface.htm.

For more information

The RotoView NLDR algorithms are protected by our patents and trade secrets. Partial implementation in our RotoView Evaluation System introduces the NLDR algorithms to potential licensees. Further information requires a Non-Disclosure Agreement. Please contact Scott LaRoche at 1+ (281) 879-6226, fax 1+ (281) 879-6415, e-mail scott@innoventions.com.

INNOVENTIONS® Inc. "INNOVATIVE PRODUCTS FROM INVENTIVE MINDS" ©2010 INNOVENTIONS, INC. All rights reserved. INNOVENTIONS, Inc. is a private company not associated with any smartphone manufacturer. Apple, the Apple logo, iPod, iPod touch, and iTunes are trademarks of Apple Inc., registered in the U.S. and other countries. iPhone is a trademark of Apple Inc. App Store is a service mark of Apple Inc. RotoView and INNOVENTIONS are registered trademarks of INNOVENTIONS, Inc.