A method for segmentation of 3D image data of a 3D image, the method comprising: • determining a first set of local features (201a, 202a, 203a, 204a) within first image data for a first view of the 3D image, wherein a local feature is a description of a patch surrounding a point in an image; • determining a second set of local features (201b, 202b, 203b, 204b) within second image data for a second view of the 3D image; • determining a set of corresponding local features between the first set of local features of the first image data and the second set of local features of the second image data of the 3D image; and • segmenting each of the first image data and the second image data into a plurality of corresponding depth regions of the first image data and second image data of the 3D image based on the set of corresponding local features within corresponding depth regions of the first image data and the second image data and a depth map of the 3D image, wherein the depth map is quantized and each depth region is formed by contiguous depth map elements having a same quantized depth value, wherein the segmenting comprises; ∘ computing, for each pair of corresponding depth regions in the first image data and the second image data, an average spatial displacement value of corresponding local features contained within the corresponding depth regions and ∘ merging adjacent depth regions within the first and within the second image data among the plurality of depth regions if a correlation value is larger than a predetermined threshold value, wherein the correlation value is calculated according to: corr = 1 − α abs D 1 − D 2 depthRange + 1 − α abs md 1 − md 2 distRange / 2 wherein α is a configurable weight parameter, D1 and D2 are respectively the quantized depth values of the two adjacent depth regions, mdi and md2 are respectively average spatial displacement values of the two adjacent depth regions among the calculated average spatial displacement values, wherein depthRange represents a full range of quantized depth values for the 3D image and distRange indicates a full range of the computed average spatial displacement values. • determining a first set of local features (201a, 202a, 203a, 204a) within first image data for a first view of the 3D image, wherein a local feature is a description of a patch surrounding a point in an image; • determining a second set of local features (201b, 202b, 203b, 204b) within second image data for a second view of the 3D image; • determining a set of corresponding local features between the first set of local features of the first image data and the second set of local features of the second image data of the 3D image; and • segmenting each of the first image data and the second image data into a plurality of corresponding depth regions of the first image data and second image data of the 3D image based on the set of corresponding local features within corresponding depth regions of the first image data and the second image data and a depth map of the 3D image, wherein the depth map is quantized and each depth region is formed by contiguous depth map elements having a same quantized depth value, wherein the segmenting comprises; ∘ computing, for each pair of corresponding depth regions in the first image data and the second image data, an average spatial displacement value of corresponding local features contained within the corresponding depth regions and ∘ merging adjacent depth regions within the first and within the second image data among the plurality of depth regions if a correlation value is larger than a predetermined threshold value, wherein the correlation value is calculated according to: corr = 1 − α abs D 1 − D 2 depthRange + 1 − α abs md 1 − md 2 distRange / 2 wherein α is a configurable weight parameter, D1 and D2 are respectively the quantized depth values of the two adjacent depth regions, mdi and md2 are respectively average spatial displacement values of the two adjacent depth regions among the calculated average spatial displacement values, wherein depthRange represents a full range of quantized depth values for the 3D image and distRange indicates a full range of the computed average spatial displacement values. ∘ computing, for each pair of corresponding depth regions in the first image data and the second image data, an average spatial displacement value of corresponding local features contained within the corresponding depth regions and ∘ merging adjacent depth regions within the first and within the second image data among the plurality of depth regions if a correlation value is larger than a predetermined threshold value, wherein the correlation value is calculated according to: corr = 1 − α abs D 1 − D 2 depthRange + 1 − α abs md 1 − md 2 distRange / 2 wherein α is a configurable weight parameter, D1 and D2 are respectively the quantized depth values of the two adjacent depth regions, mdi and md2 are respectively average spatial displacement values of the two adjacent depth regions among the calculated average spatial displacement values, wherein depthRange represents a full range of quantized depth values for the 3D image and distRange indicates a full range of the computed average spatial displacement values.