Objective

2

Three dimensional video has attracted considerable attention from the image processing community due to its satisfactory performance in various applications

including 3D television

free-view television

free-view video

and immersive teleconference.Compared with traditional block-based techniques

object-based methods have the merits of flexible interactivity and efficient resource usage and are thus favored in many practical applications.Hence

object-based 3D video

whose efficient shape coding is a key technique in practical applications

is an important developing trend.Shape coding has been considerably studied

and many methods have been proposed.However

most of the existing shape coding methods are mainly proposed for image or video shape coding and seldom for 3D video shape coding.A straightforward approach to encoding the shapes of 3D video objects is through the use of the same techniques for image or video objects.However

this method of coding does not completely exploit the redundancy among 3D shape videos

thus resulting in poor coding efficiency.Strong inter-frame redundancy exists across time and view directions in a 3D video sequence.Therefore

most of the existing 3D video coding schemes jointly adopt motion-compensated prediction (MCP) and disparity-compensated prediction (DCP) techniques to achieve high coding efficiency.3D video and 3D shape video share certain similarities; thus

correlations may also exist among object contours across time and view directions

which may be exploited in shape coding to improve coding efficiency.Hence

with this speculation and consideration of the requirements of practical object-based 3D video applications

an efficient multi-mode 3D video shape coding scheme is proposed in this study.This scheme is based on contour and chain representation

where the correlation among object contours across time and view directions is exploited to achieve high coding efficiency.

Method

2

For a given 3D shape image

the contours of visual objects are first extracted and preprocessed frame by frame to create perfect single-pixel width.That is

the object contours are 8-connected and only one path exists between any two neighboring contour points.A new metric called shape activity is then applied to assess the shape variation of objects within each frame.On the basis of this assessment

the entire frames are classified into two categories:intra-coding and predictive inter-coding frames.If the shape activity within a frame is large

then intra-coding will be implemented; otherwise

intra-coding will be conducted.For an intra-coding frame

it is encoded on the basis of linearity and direction constraints within chain links to achieve high coding efficiency.For an inter-coding frame

it is encoded using one of the three coding modes

namely

contour-based MCP

DCP

or joint MCP and DCP

to efficiently remove the intra-view temporal correlation and the inter-view spatial correlation among object contours and improve coding efficiency.The principles of MCP and DCP for 3D shape video are similar to those for 3D video.However

the correlation among object contours is dissimilar to that between video textures.In 3D video

the textures are two dimensional

whereas object contour is one dimensional.Video textures can generally be viewed as rigid

whereas the shape of an object contour often changes non-regularly.Usually

a small variation of object contour in a frame may considerably decrease the correlation between consecutive frames.In addition

correlations may decrease more quickly than textures with an increase in time interval.Hence

conventional prediction techniques for 3D video are unsuitable for 3D shape video.In our coding scheme

a new prediction structure is developed to effectively exploit the intra-view temporal correlation and the inter-view spatial correlation among object contours to efficiently encode 3D shape video.

Result

2

Experiments are conducted to evaluate the performance of the proposed scheme

and results of partial comparison with several well-known methods are presented.The experimental results show that our scheme outperforms classic and state-of-the-art methods and the average compression efficiency can be improved by 9.3% to 64.8%.

Conclusion

2

The proposed scheme can effectively remove the intra-view temporal correlation and the inter-view spatial correlation among object contours.This scheme can also achieve high coding efficiency that outperforms those of existing methods and has potential in many object-based image and video applications

such as object-based coding

editing

and retrieval.