Patent Application
20140160241
This invention relates to a bitstream syntax and semantics of repetitive structure discovery based 3D model compression algorithm, a method and an apparatus for encoding the same, and a method and an apparatus for decoding the same.
In practical applications, many 3D models consist of a large number of connected components. And these multi-connected 3D models usually contain lots of repetitive structures in various transformations, as shown in
An efficient compression algorithm for multi-connected 3D models, by taking advantage of discovering repetitive structures in the input models, was proposed in “Efficient Compression Scheme for Large 3D Engineering Models,” WO 2010149492, filed Jun. 9, 2010, and assigned to Thomson Licensing, and whose teachings are incorporated herein by reference. It discovers the structures repeating in various positions, orientations and scaling factors. Then the 3D model is organized into a “pattern-instance” representation. A pattern is the representative geometry of the corresponding repetitive structure. The connected components belonging to a repetitive structure are called instances of the corresponding pattern and are represented by their transformation, i.e. the positions, orientations and possible scaling factors, regarding to the pattern. The orientation of an instance is represented by two orthogonal axes represented by (x0, y0, z0) and (x1, y1, z1) in a Cartesian coordinate system, or (alpha, beta, gamma) in a spherical coordinate system.
A compressed bitstream syntax and semantics is disclosed that relates to a repetitive structure discovery based compression algorithm, which has been proven to be more efficient than the static 3D model compression algorithms provided by MPEG-3DGC. The disclosed compressed bitstream syntax and semantics of our repetitive structure discovery based compression algorithm is applicable, for example, to MPEG.
The present invention is about the compressed bitstream syntax and semantics.
The present invention also provides a system and a method for encoding and decoding a bitstream for a 3D model having repetitive structures.
An apparatus that utilizes the method is disclosed below.
The present invention also provides a computer readable medium having executable instructions to cause a computer to perform a method comprising corresponding steps for encoding or decoding a bitstream for a 3D model having repetitive structures.
Three-dimensional (3D) meshes are widely used in various applications for representing 3D objects, such as video games, engineering design, e-commerce, virtual reality, and architectural and scientific visualization. Usually their raw representation requires a huge amount of data. However, most applications prefer compact 3D mesh representation for storage or transmission. Typically, 3D meshes are represented by three types of data: connectivity data, geometry data and property data. Connectivity data describe the adjacency relationship between vertices, geometry data specify vertex locations, and property data specify attributes such as the normal vector, material reflectance and texture coordinates. Most 3D compression algorithms compress connectivity data and geometry data separately. The coding order of geometry data is determined by the underlying connectivity coding. Geometry data is usually compressed by three main steps: quantization, prediction and statistical encoding. 3D mesh property data are usually compressed in a similar manner.
The present invention is related to an efficient compression method for large 3D engineering models. Such models are often composed of several partitions, so-called “connected components”. The redundancy in the representation of repeating geometric feature patterns can be reduced by regarding all the connected components that are equivalent (e.g. after normalization of position, size) as instances of one geometry pattern. Equivalent components can be clustered. A cluster may refer to only some, or to all components of a 3D model. Then each connected component can be represented by an identifier, such as an alphanumeric identifier, of the corresponding geometry pattern (or clustering class) and the transformation information which can reconstruct the component from the geometry pattern. This transformation information may exemplarily comprise one or more of scale factors, mean (or center), orientation axes (or and rotation information, respectively), or shift information. In principle, also others are possible.
The encoded model can be represented, transmitted and/or stored as a bitstream.
While we want the bitstream to embed all the transformation data, we also want it to be efficient and to address several applications, where sometimes either bitstream size or decoding efficiency or error resilience matters the most.
Therefore, two options are disclosed for how to put the transformation data of one instance, i.e. its position, orientation and scaling factor, in the bitstream. Both of them have their own advantages. An adaptive combination of both is particularly advantageous.
Option (A) is called grouped instance transformation mode: Using this mode, the position, orientation and possible scaling factor of one instance are packed together in the bitstream.
Advantages of option (A) are
Option (B) is called separate instance transformation mode: The positions, orientations or possible scaling factors of all instances are packed together in the bitstream. In other words, the position, orientation and possible scaling factor of one instance are packed separately in the bitstream.
Advantages of option (B) are
A decoder that uses option (B) has also the following features.
Our bitstream definition includes both the above two options (A) and (B). Then the user, or an automatic control, can choose the one which fits their one or more applications better.
The general structure of the compressed bitstream of our repetitive structure discovery based compression algorithm, A3DMC, is as shown in
The bitstream starts with the header buffer (A3DMC_stream_header), which contains all the necessary information for decoding the compressed stream: whether there is any repetitive structure in the original model, the 3D model compression method used for compressing patterns and other parts if necessary, whether the “grouped instance transformation mode” or “separate instance transformation mode” is used in this bitstream, whether there are some parts of the original model which are not included in any repetitive structure (unique part), etc.
If there is no repetitive structure in the original model (repeat_struc_bit !=1), the left part (e.g. the beginning) of the bitstream is the compressed input 3D model using the 3D model compression method indicated in A3DMC_stream_header. Otherwise, the next part in the bitstream is the compressed result of all patterns. Depending on which instance transformation packing mode is chosen in this bitstream, either compr_insta_grouped_data or compr_insta_separate_data is the next part in the bitstream. If there is unique part in the original 3D model, compr_uni_part_data is attached. Otherwise, the bitstream ends.
The compressed bitstream syntax and semantics of A3DMC, will be explained in details as follows.
f(n): fixed-pattern bit string using n bits written (from left to right). n depends on the code length for each symbol
ec(v): entropy-coded (e.g., arithmetic coded) syntax element, including possibly configuration symbols.
pattern_num—2: a 16-bit unsigned integer indicating the number of all patterns if it is not less than 255. In this case, the total pattern number is (pattern_num—2+255)
instance_num: a 16-bit unsigned integer indicating the number of all instances if it is less than 65535. The minimum value of instance_num is 1.
instance_num—2: a 32-bit unsigned integer indicating the number of all instances if it is not less than 65535. In this case, the total instance number is (instance_num—2+65535)
insta_trans_group_bit: a 1-bit unsigned integer indicating whether “grouped instance transformation mode” or “separate instance transformation mode” is used in this bitstream. 0 for “separate instance transformation mode” and 1 for “grouped instance transformation mode”.
insta_orient_mode_bit: a 1-bit unsigned integer indicating the encoding mode of instance orientation. 0 means spherical mode and 1 Cartesian mode.
use_scaling_bit: a 1-bit unsigned integer indicating whether instance transformation include scaling factors. 0 for scaling factors being included in instance transformation and 1 for not.
uni_part_bit: a 1-bit unsigned integer indicates whether there is unique part in the original 3D model. 0 means there is no unique part and 1 means there is unique part.
reserved_bits: a 4-bit unsigned integer which is always 0000 and used for byte alignment.
Additionally, the bitstream described above may also be embedded in other bitstreams such as the SC3DMC bitstream defined by MPEG-3DGC [w11455]. Here is a possible embodiment of that solution.
We use the ISO reserved value 3 of encodingMode of SC3DMCStreamHeader as follows (Ref. to the original Table 53 of [w11455]).
We revise SC3DMCStream defined in [w11455] as follows.
In particular, the invention relates to
The implementations described herein may be implemented in, for example, a method or a process, an apparatus, a software program, a data stream, or a signal. Even if only discussed in the context of a single form of implementation (for example, discussed only as a method), the implementation of features discussed may also be implemented in other forms (for example, an apparatus or program). An apparatus may be implemented in, for example, appropriate hardware, software, and firmware. The methods may be implemented in, for example, an apparatus such as, for example, a processor, which refers to processing devices in general, including, for example, a computer, a microprocessor, an integrated circuit, or a programmable logic device. Processors also include communication devices, such as, for example, computers, cell phones, portable/personal digital assistants (“PDAs”), and other devices that facilitate communication of information between end-users.
Reference to “one embodiment” or “an embodiment” or “one implementation” or “an implementation” of the present principles, as well as other variations thereof, mean that a particular feature, structure, characteristic, and so forth described in connection with the embodiment is included in at least one embodiment of the present principles. Thus, the appearances of the phrase “in one embodiment” or “in an embodiment” or “in one implementation” or “in an implementation”, as well any other variations, appearing in various places throughout the specification are not necessarily all referring to the same embodiment.
As will be evident to one of skill in the art, implementations may produce a variety of signals formatted to carry information that may be, for example, stored or transmitted. The information may include, for example, instructions for performing a method, or data produced by one of the described implementations. For example, a signal may be formatted to carry the bitstream of a described embodiment. Such a signal may be formatted, for example, as an electromagnetic wave (for example, using a radio frequency portion of spectrum) or as a baseband signal. The formatting may include, for example, encoding a data stream and modulating a carrier with the encoded data stream. The information that the signal carries may be, for example, analog or digital information. The signal may be transmitted over a variety of different wired or wireless links, as is known. The signal may be stored on a processor-readable medium.
In principle, the disclosed invention can also be applied to other data compression areas. The invention results in a unique bitstream format.
While the bitstream embeds all the transformation data, it is efficient and may address several applications, where sometimes either bitstream size or decoding efficiency or error resilience matters the most. Therefore, two mode options are disclosed for how to put the transformation data of one instance, i.e. its position, orientation and scaling factor, in the bitstream. In the first mode (Option A), the position, orientation and possible scaling factor of one instance are packed together in the bitstream. In the second mode (Option B), the positions, orientations or possible scaling factors of all instances are packed together in the bitstream.
It will be understood that the present invention has been described purely by way of example, and modifications of detail can be made without departing from the scope of the invention.
Each feature disclosed in the description and (where appropriate) the claims and drawings may be provided independently or in any appropriate combination. Features may, where appropriate be implemented in hardware, software, or a combination of the two. Connections may, where applicable, be implemented as wireless connections or wired, not necessarily direct or dedicated, connections. Reference numerals appearing in the claims are by way of illustration only and shall have no limiting effect on the scope of the claims.
| Number | Date | Country | Kind |
|---|---|---|---|
| PCT/CN2011/076991 | Jul 2011 | CN | national |
| Filing Document | Filing Date | Country | Kind | 371c Date |
|---|---|---|---|---|
| PCT/CN2012/078301 | 7/6/2012 | WO | 00 | 1/7/2014 |
