Tracking of Non-Rigid Object in Complex Wavelet Domain

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specified by the non-zero points of Mt + x. that is for a

given translation x, for each non-zero pixel p of Mt find

the location p + x of Dt + 1. The Kth largest of these m

values found so for is the partial directed Hausdorff dis-

tance hK(Mt + x, It + 1).

3.3. Updating the Model

The new model, Mt + 1 constructed from finding the

translation x of Mt with respect to the It + 1 by selectively

choosing the non zero pixels of It + 1 which falls within a

distance of

of non zero pixels of Mtx. This can be

obtained by dialating Mt by a disc radius

, shifting this

by x, and then computing the logical AND of It + 1 with

the dialated and translated model.

4. Experimental Results

The initial model, corresponding to the first frame of the

image sequence is taken. The user needs to take a rectan-

gle in the first frame containing this initial model. Then

image is processed to select the subset of the edge pixels

in this rectangle. This is done by assuming that the cam-

era will not move in first two consecutive frames and

using this fact to filter the first image frame based on the

second image frame. Those edge pixels in the user se-

lected rectangle that moved between the first and the

second frame are used as initial model. Thus the only

input from the user is the rectangle in the first frame of

the image sequence that contains the moving object.

The proposed method of tracking of non-rigid object is

applied on various videos and the results are compared

by computing the dual tree complex wavelet coefficient

to that by real and spatial domain coefficients. It has been

observed that:

In spatial domain, tracking is more accurate but

high execution time

In real wavelet domain, tracking is not as good as

in the spatial domain but the execution time is ap-

proximately 4 times less

Tracking in Complex wavelet domain is not only

fast as compared to real wavelet domain but also it

is comparable to spatial domain.

Also, we observed that in the spatial domain and real

wavelet domain the tracking work well up to the 15

frames and thereafter tracker is not able to track the ob-

ject accurately while as in complex wavelet domain it is

more accurate and efficient. Here the results are only

mentioned up to the 40 frames. The comparative results

for two representative videos are presented: in spatial

domain, real wavelet domain and dual tree complex

wavelet domain in Figure 2 and Figure 3.

5. Conclusions and Future Scope

The experiments are performed on various moving vid-

eos and non-rigid objects are tracked in spatial domain,

real wavelet domain and in complex wavelet domain.

Comparing the tracking results in three domains, we

found that the tracking in spatial domain is very accurate

because the operations are performed pixel-wise basis

but the computational time in spatial domain is high. It

has been observed that in real wavelet domain, the com-

putational complexity is low (approximately 4 times less)

but results of tracking are very poor. Tracking in com-

plex wavelet domain is fast as well as it produce good

results as compared to real wavelet domain. Here in

complex wavelet domain, both real as well as imaginary

components are taken which provide us better segmenta-

tion and tracking as compared to that of real wavelets.

The proposed tracking algorithm can be extended for

tracking of multiple objects in video sequences.

6. Acknowledgements

The authors are thankful to the Department of Science &

Technology, New Delhi and the University Grants

Commission (UGC), New Delhi, India for providing re-

search grant vide its grant nos. SF/FTP/ETA-023/2009

and 36-246/2008( SR) for research project.

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