Beijing Xiaomi Mobile Software Co., Ltd.

Sebastien Lasserre

Jonathan Taquet

Mary-Luc Georges Henry Champel

Shuo Gao

A method of encoding/decoding a point cloud into/from a bitstream of encoded point cloud data representing a physical object includes determining a dynamic list of at least one prediction data used to derive at least one candidate predictor used to encode geometry data of points of the point cloud. The list of at least one prediction data is dynamic because during the encoding of points, prediction data are updated based on residuals radius of decoded points.

Method and apparatus of encoding/decoding point cloud geometry data captured by a spinning sensors head

A method of encoding a point cloud into a bitstream of encoded point cloud data representing a physical object is provided. The method includes an azimuthal coding mode providing a series of bits for encoding a coordinate of a point of the point cloud. The method includes: dividing a parent interval, to which the point coordinate belongs to, into a left half interval and a right half interval; interpolating a left angle (φ), associated with the left half interval, and a right angle (φ), associated with the right half interval, from at least one inherited angle associated with the parent interval; selecting a context depending on the left angle (φ) and the right angle (φ); and context-adaptive binary entropy encoding a bit (b), into the bitstream, based on the selected context, the coded bit (b) indicating which of the two half intervals the point coordinate belongs to.

Method and apparatus of encoding/decoding point cloud geometry data using azimuthal coding mode

There is provided methods and apparatus of encoding/decoding a point cloud representing a physical object. Points are captured by a spinning sensors head and are represented by sensor indices associated with sensors that captured the points, azimuthal angles representing capture angles of said sensors, and radius values of spherical coordinates of the point. Points are ordered based order indices obtained from the azimuthal angles and the sensor indices. Order index differences are encoded. An order index difference represents a difference between order indices associated with two consecutive ordered points. Optionally, the method encodes radius values, residual azimuthal angles associated with ordered points and residuals of three-dimensional cartesian coordinates of ordered points based on their three-dimensional cartesian coordinates, decoded azimuthal angles based on azimuthal angles, decoded radius values and sensor indices.

A method of encoding, into a bitstream, point cloud geometry data sensed by at least one sensor associated with a sensor index, includes: obtaining a list of candidate radiuses (L={r}) for a first occupied coarse point (P) having a first sensor index (λ), a first sample index (s) and being associated with a first radius (r); selecting, for the first occupied coarse point (P), a selected predicting radius (r) from the list of candidate radiuses (L={r}); encoding, in the bitstream, a data (I) representative of the selected predicting radius (r) in the list of candidate radiuses (L={r}); and predictively encoding, in the bitstream, a residual radius (r) between the first radius (r) and the selected predicting radius (r).

Cloud geometry data sensed by at least one sensor

There is provided methods and apparatus of encoding/decoding a point cloud captured by a set of sensors. The encoding method obtains a list of ordered points of the point cloud by ordering the points according to a lexicographic order based on azimuthal angles and sensor indices associated with points of the point cloud; obtains a next point following a current point in the list of ordered points and having an order index different of an order index of the current point, and obtains a number of duplicated points equals to a number of points following the current point that have an order index equals to the order index of the current point; encodes the number of duplicated points and encodes an order index difference representing a difference between the order index of the next point and the order index of the current point.

Method and apparatus of encoding/decoding point cloud captured by a spinning sensors head

There is provided methods and apparatus of encoding/decoding a point cloud into/from a bitstream of encoded point cloud data representing a physical object, each point of the point cloud being associated with spherical coordinates representing an azimuthal angle responsive to a capture angle of a sensor that captured the point and a radius responsive of a distance of the point from a referential. The encoding method includes adaptively quantizing a residual error azimuthal angle, derived from the azimuthal angle, based on the radius.

Method and apparatus of quantizing spherical coordinates used for encoding/decoding point cloud geometry data

A method of encoding, into a bitstream, point cloud geometry data represented by ordered coarse points occupying some discrete positions of a set of discrete positions of a two-dimensional space, includes: encoding, into the bitstream, a data (S) indicating if an occupied coarse point (P) associated with a point of the point cloud is a late occupied coarse point; and if the data (S) indicates that the occupied coarse point is a late occupied coarse point (P), obtaining a late point order index difference (Δo) between an order index of the late occupied coarse point (P), and an order index of a second reference coarse point (P'); and encoding, into the bitstream, an amplitude of the late point order index difference.

Method and apparatus of encoding/decoding point cloud geometry data sensed by at least one sensor

A method of encoding, into a bitstream, point cloud geometry data sensed by at least one sensor associated with a sensor index is provided, the point cloud geometry data being represented by ordered coarse points occupying some discrete positions of a set of discrete positions of a two-dimensional space, each coarse point being located within the two-dimensional space by an order index defined from a sensor index associated with a sensor that is able to sense a point of the point cloud represented by the coarse point and a sample index associated with a sensing time instant at which the point of the point cloud is sensed. The method includes: obtaining sensing coverage data (SCD) representative of at least one range of order indexes associated with sensed data; and encoding the sensing coverage data (SCD) into the bitstream.

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Beijing, China

Sebastien Lasserre