System and method for tracking objects
AssigneeGM Global Technology Operations LLC
InventorsShuqing Zeng, Yuanhong Li
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Abstract
A method for tracking an object, by generating kinematic models corresponding to the object using a computerized object-tracking system, is disclosed. The method includes receiving, by a data collection module, scan data associated with an object, and generating by the module, using the scan data, a new frame F, associated with a new time t+dt and including new points X. A clustering module identifies a new group G of new points Xi of the new frame F. A data association module associates the new group G with the object based on previous information associated with the object. A tracking module determines a new kinematic model M corresponding to the object based on the new group G.
Claims20
A non-transitory computer-readable storage device comprising instructions that, when executed by a processor, cause the processor to perform operations, for tracking from a vehicle, an object by generating kinematic models corresponding to the object, comprising:
- receiving scan data associated with the object;
- generating, using the scan data, a new frame F, associated with a new time t+dt and including new points X;
- identifying a new group G of new points Xi, of the new points X of the new frame F, where i=1, . . . , N, with N being a positive integer corresponding to a number of the new points;
- associating the new group G with the object based on previous information associated with the object;
- and
- determining, based on the new group G, a new kinematic model M corresponding to the object;
- wherein:
- determining, based on the new group G, the new kinematic model M corresponding to the object includes generating a predicted group Gp;
- determining the new kinematic model M includes iteratively matching the predicted group Gp to the new group G;
- iteratively matching the predicted group Gp to the new group G includes determining an initial translation adjustment vector ΔT and iteratively adjusting a translation vector T using the initial translation adjustment vector ΔT;
- and
- determining the initial translation adjustment vector ΔT is performed using at least one of:
- a localized point-matching technique;
- and
- a maximum-likelihood technique.
A non-transitory computer-readable storage device comprising instructions that, when executed by a processor, cause the processor to perform operations, for tracking from a vehicle, an object by generating kinematic models corresponding to the object, comprising:
- receiving scan data associated with the object;
- generating, using the scan data, a new frame F, associated with a new time t+dt and including new points X;
- identifying a new group G of new points Xi, of the new points X of the new frame F, where i=1, . . . , N, with N being a positive integer corresponding to a number of the new points;
- associating the new group G with the object based on previous information associated with the object;
- and
- determining, based on the new group G, a new kinematic model M corresponding to the object;
- wherein:
- determining, based on the new group G, the new kinematic model M corresponding to the object includes generating a predicted group Gp;
- determining the new kinematic model M includes iteratively matching the predicted group Gp to the new group G;
- iteratively matching the predicted group Gp to the new group G includes determining an initial translation adjustment vector ΔT, and iteratively adjusting a translation vector T using the initial translation adjustment vector ΔT;
- if the magnitude of the translation adjustment vector ΔT is above a predetermined threshold the iterated translation vector T′ is further iterated;
- and
- if the magnitude of the translation adjustment vector ΔT is within the predetermined threshold, the iterated translation vector T′ is used to determine parameters of the new kinematic model M, including using components dx′, dy′ of the iterated translation vector T′ to determine a velocity Vt and an angle of velocity θt for the new kinematic model M according to relationships represented as:
- V
- t
- =
- dx
- 2
- +
- dy
- 2
- δ
-
-
- t
-
-
- and
-
-
- θ
- t
- =
- arc
-
-
- tan
-
- (
- dy
- dx
- )
- .
A non-transitory computer-readable storage device comprising instructions that, when executed by a processor, cause the processor to perform operations, for tracking from a vehicle, an object by generating kinematic models corresponding to the object, object, comprising:
- receiving scan data associated with the object;
- generating, using the scan data, a new frame F, associated with a new time t+dt and including new points X;
- identifying a new group G of new points Xi, of the new points X of the new frame F, where i=1, . . . , N, with N being a positive integer corresponding to a number of the new points;
- associating the new group G with the object based on previous information associated with the object;
- and
- determining, based on the new group G, a new kinematic model M corresponding to the object;
- wherein:
- determining, based on the new group G, the new kinematic model M corresponding to the object includes generating a predicted group Gp;
- generating the predicted group Gp is performed as a function of a previous kinematic model representing the object, the new group G, and a translation vector T;
- the predicted group Gp corresponds to a future time t+δt, and is determined according to:
- Gt+δtp=Gt+Tt|δt;
- GP represents the predicted group Gp;
- GPt+δt represents the predicted group in association with the future time t+δt;
- Tt|δt represents the translation vector T;
- the translation vector Tt|δt includes an x-direction translation component dx and a y-direction translation component dy;
- the translation components are determined as a function of a velocity Vt and a velocity direction θt of the previous kinematic model representing the object;
- the translation components dx, dy are related to the velocity Vt and the velocity direction θt of the previous kinematic model representing the object according to:
- T
- t
-
- δ
-
-
- t
- =
- [
- dx
- dy
- ]
-
- I
- N
- =
- [
- V
- t
-
- cos
-
- (
- θ
- t
- )
-
- dt
- V
- t
-
- sin
-
- (
- θ
- t
- )
-
- dt
- ]
-
- I
- N
- ;
- and
- IN is an identity matrix.
Dependencies are inferred from the claim text.