Method and apparatus of encoding/decoding series of data

1 . A method of encoding a series of data, into a bitstream, the method comprising:

obtaining a current neighborhood configuration (i) of a set of candidate neighborhood configurations (I) relative to a current data of the series of data, the set of candidate neighborhood configurations being obtained from previously encoded data of the series of data;

obtaining a reduced current neighborhood configuration (i′) by applying a dynamic reduction function (DR n ) to the current neighborhood configuration (i), an image of the dynamic reduction function being a set of reduced neighborhood configurations and each reduced neighborhood configuration being associated with a leaf node of a tree; the reduced current neighborhood configuration (i′) being obtained by progressing from a root node of the tree until a leaf node based on values of constitutive elements of the current neighborhood configuration (i);

encoding the current data by using an entropy coder of a set of entropy coders, the entropy coder being selected based on the reduced current neighborhood configuration (i′);

incrementing a number of use relative to the use of the reduced current neighborhood configuration (i′); and

if the number of use exceeds a threshold,

updating the dynamic reduction function (DR n ) by

replacing the reduced neighborhood configuration (i′) in the image of the dynamic reduction function (DR n ) by at least two new reduced neighborhood configurations;

obtaining a new tree from the tree by attaching at least two new leaf nodes, associated with the at least two new reduced neighborhood configurations, to an old leaf node associated with the reduced neighborhood configuration (i′); and

initializing a number of use relative to the use of each new reduced neighborhood configuration.

2 . The method of claim 1 , wherein the current neighborhood configuration (i) comprises a primary neighborhood configuration (i 1 ) and a secondary neighborhood configuration (i 2 ), and the reduced current neighborhood configuration (i′) is obtained as a compound of the primary neighborhood configuration (i 1 ) and a reduced secondary neighborhood configuration (i 2 ′) obtained by applying the dynamic reduction function to the secondary neighborhood configuration (i 2 ).

3 . The method of claim 1 , wherein the number of use relative to the use of the reduced current neighborhood configuration (i′) indicates a number of times the reduced current neighborhood configuration (i′) has been used for previously encoding data of the series of data.

4 . The method of claim 1 , wherein the number of use relative to the use of the reduced current neighborhood configuration (i′) indicates a number of times a primary data (i 1 ), comprised in neighborhood configurations of images of dynamic reduction functions, has been used for previously encoding data of the series of data.

5 . The method of claim 1 , wherein the number of use is stored in an array.

6 . The method of claim 2 , wherein the secondary neighborhood configuration (i 2 ) comprises an ordered series of elements and the reduced secondary neighborhood configuration (i 2 ′) is defined by keeping k n first elements of the secondary neighborhood configuration (i 2 ), where k n is a given integer number.

7 . The method of claim 6 , wherein the number k n is stored in an array.

8 . The method of claim 6 , wherein the number k n depends on the primary neighborhood configuration and the reduced secondary neighborhood configuration (i 2 ′), or depends on the primary neighborhood configuration (i 1 ).

9 . The method of claim 6 , wherein the number k n and the number of use depend on the first secondary neighborhood configuration (i 1 ) and the reduced secondary neighborhood configuration (i 2 ′) down to a given depth (d max ) of the tree and depend only on the primary neighborhood configuration (i 1 ) from said depth (d max ).

10 . An apparatus of encoding a series of data into a bitstream of encoded point cloud data representing a physical object, the apparatus comprising at least one processor configured to:

obtain a current neighborhood configuration (i) of a set of candidate neighborhood configurations (I) relative to a current data of the series of data, the set of candidate neighborhood configurations being obtained from previously encoded data of the series of data;

obtain a reduced current neighborhood configuration (i′) by applying a dynamic reduction function (DR n ) to the current neighborhood configuration (i), the image of the dynamic reduction function being a set of reduced neighborhood configurations and each reduced neighborhood configuration being associated with a leaf node of a tree; the reduced current neighborhood configuration (i′) being obtained by progressing from a root node of the tree until a leaf node based on values of constitutive elements of the current neighborhood configuration (i);

encode the current data by using an entropy coder of a set of entropy coders, the entropy coder being selected based on the reduced current neighborhood configuration (i′);

increment a number of use relative to the use of the reduced current neighborhood configuration (i′); and

if the number of use exceeds a threshold,

update the dynamic reduction function (DR n ) by

replacing the reduced neighborhood configuration (i′) in an image of the dynamic reduction function (DR n ) by at least two new reduced neighborhood configurations;

obtaining a new tree from the tree by attaching at least two new leaf nodes, associated with the at least two new reduced neighborhood configurations, to an old leaf node associated with the reduced neighborhood configuration (i′); and

initializing a number of use relative to the use of each new reduced neighborhood configuration.

11 . A method of decoding a series of data, from a bitstream, the method comprising:

obtaining a current neighborhood configuration (i) of a set of candidate neighborhood configurations (I) relative to a current data of the series of data, the set of candidate neighborhood configurations being obtained from previously decoded data of the series of data;

obtaining a reduced current neighborhood configuration (i′) by applying a dynamic reduction function (DR n ) to the current neighborhood configuration (i), an image of the dynamic reduction function being a set of reduced neighborhood configurations and each reduced neighborhood configuration being associated with a leaf node of a tree, the reduced current neighborhood configuration (i′) being obtained by progressing from a root node of the tree until a leaf node based on values of constitutive elements of the current neighborhood configuration (i);

decoding the current data by using an entropy decoder of a set of entropy decoders, the entropy decoder being selected based on the reduced current neighborhood configuration (i′);

incrementing a number of use relative to the use of the reduced current neighborhood configuration (i′); and

if the number of use exceeds a threshold,

updating the dynamic reduction function (DR n ) by

replacing the reduced neighborhood configuration (i′) in the image of the dynamic reduction function (DR n ) by at least two new reduced neighborhood configurations;

obtaining a new tree from the tree by attaching at least two new leaf nodes, associated with the at least two new reduced neighborhood configurations, to an old leaf node associated with the reduced neighborhood configuration (i′); and

initializing a number of use relative to the use of each new reduced neighborhood configuration.

12 . The method of claim 11 , wherein the current neighborhood configuration (i) comprises a primary neighborhood configuration (i 1 ) and a secondary neighborhood configuration (i 2 ), and the reduced current neighborhood configuration (i′) is obtained as a compound of the primary neighborhood configuration (i 1 ) and a reduced secondary neighborhood configuration (i 2 ′) obtained by applying the dynamic reduction function to the secondary neighborhood configuration (i 2 ).

13 . The method of claim 11 , wherein the number of use relative to the use of the reduced current neighborhood configuration (i′) indicates a number of times the reduced current neighborhood configuration (i′) has been used for previously decoding data of the series of data.

14 . The method of claim 11 , wherein the number of use relative to the use of the reduced current neighborhood configuration (i′) indicates a number of times a primary data (i 1 ), comprised in neighborhood configurations of images of dynamic reduction functions, has been used for previously decoding data of the series of data.

15 . The method of claim 11 , wherein the number of use is stored in an array.

16 . The method of claim 12 , wherein the secondary neighborhood configuration (i 2 ) comprises an ordered series of elements and the reduced secondary neighborhood configuration (i 2 ′) is defined by keeping k n first elements of the secondary neighborhood configuration (i 2 ), where k n is a given integer number.

17 . The method of claim 16 , wherein the number k n is stored in an array.

18 . The method of claim 16 , wherein the number k n depends on the primary neighborhood configuration and the reduced secondary neighborhood configuration (i 2 ′), or depends on the primary neighborhood configuration (i 1 ).

19 . The method of claim 16 , wherein the number k n and the number of use depend on the first secondary neighborhood configuration (i 1 ) and the reduced secondary neighborhood configuration (i 2 ′) down to a given depth (d max ) of the tree and depend only on the primary neighborhood configuration (i 1 ) from the depth (d max ).

20 . An apparatus of decoding a series of data from a bitstream of encoded point cloud data, the apparatus comprising at least one processor configured to perform the method of claim 11 .