# US 9,519,060 B2 · Methods and systems for vehicle classification from laser scans using global alignment

> Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt

- Number: US 9,519,060 B2
- Document ID: US9519060B2
- Status: Granted
- Kind: B2
- Application number: 14/287,538
- Filed: 2014-05-27
- Published: 2015-12-03
- Granted: 2016-12-13
- Earliest claimed: 2014-05-27
- Assignees: Xerox Corporation
- Applicants: Xerox Corporation
- Inventors: Boris Chidlovskii; Gabriela Csurka; Jose Antonio Rodriguez Serrano
- Web page: https://patentgrep.com/patent/US9519060B2

## CPC

- G01S 17/88: Lidar systems specially adapted for specific applications
- G01S 7/4802: {using analysis of echo signal for target characterisation; Target signature; Target cross-section}
- G01S 17/42: Simultaneous measurement of distance and other co-ordinates (indirect measurement G01S17/46)
- G01S 17/89: for mapping or imaging
- G06T 7/00: Image analysis
- G06T 7/30: Determination of transform parameters for the alignment of images, i.e. image registration
- G06V 10/754: {involving a deformation of the sample pattern or of the reference pattern; Elastic matching}
- G06V 20/58: Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
- G06T 2207/10028: Range image; Depth image; 3D point clouds
- G01S: RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING

## Abstract

A system and method for classifying vehicles from laser scan data by receiving laser scan data corresponding to multiple vehicles from a laser scanner; extracting vehicle shapes corresponding to the multiple vehicles based on the laser scan data; aligning the vehicle shapes; and generating vehicle profiles based on the aligned vehicle shapes. The system and method can further include aligning the vehicle shapes using sequence kernels, such as global alignment kernels, and constraining the sequence kernels based on determined weights.

## Claims

### Claim 1

A method for classifying vehicles comprising:
receiving laser scan data corresponding to a plurality of vehicles;
extracting, based on the laser scan data, a plurality of vehicle shapes corresponding to the plurality of vehicles;
aligning the plurality of vehicle shapes to generate a plurality of aligned vehicle shapes, wherein aligning the plurality of vehicle shapes comprises aligning the plurality of vehicle shapes using sequence kernels; and
generating one or more vehicle profiles based on the aligned vehicle shapes.

### Claim 2 (depends on 1)

The method of claim 1, wherein the sequence kernels are global alignment kernels.

### Claim 3 (depends on 2)

The method of claim 2, wherein sets of alignments corresponding to the global alignment kernels are constrained based on determined weights.

### Claim 4 (depends on 1)

The method of claim 1, further comprising classifying the plurality of vehicles by comparing the plurality of aligned vehicle shapes to the one or more vehicle profiles.

### Claim 5 (depends on 1)

The method of claim 1, further comprising:
receiving additional laser scan data corresponding to at least one additional vehicle;
extracting, based on the additional laser scan data, at least one additional vehicle shape corresponding to the at least one additional vehicle; and
classifying the at least one additional vehicle by comparing the at least one additional vehicle shape to the one or more vehicle profiles.

### Claim 6 (depends on 1)

The method of claim 1, wherein the plurality of vehicle shapes are two-dimensional shapes.

### Claim 7 (depends on 1)

The method of claim 1, wherein the plurality of vehicle shapes are three-dimensional shapes.

### Claim 8 (depends on 1)

The method of claim 1, further comprising, prior to extracting the plurality of vehicle shapes, replacing missing data in the laser scan data using interpolation based on the missing data's neighbor in the laser scan data.

### Claim 9 (depends on 1)

The method of claim 1, further comprising identifying and extracting data corresponding to vehicles of interest in the laser scan data, wherein extracting, based on the laser scan data, the plurality of vehicle shapes comprises extracting the plurality of vehicle shapes from the extracted data.

### Claim 10

A system for classifying vehicles comprising:
a processing system comprising one or more processors; and
a memory system comprising one or more computer-readable media, wherein the one or more computer-readable media contain instructions that, when executed by the processing system, cause the processing system to perform operations comprising:
receiving laser scan data corresponding to a plurality of vehicles;
extracting, based on the laser scan data, a plurality of vehicle shapes corresponding to the plurality of vehicles;
aligning the plurality of vehicle shapes to generate a plurality of aligned vehicle shapes, wherein aligning the plurality of vehicle shapes comprises aligning the plurality of vehicle shapes using sequence kernels; and
generating one or more vehicle profiles based on the aligned vehicle shapes.

### Claim 11 (depends on 10)

The system of claim 10, wherein the sequence kernels are global alignment kernels.

### Claim 12 (depends on 11)

The system of claim 11, wherein sets of alignments corresponding to the global alignment kernels are constrained based on determined weights.

### Claim 13 (depends on 10)

The system of claim 10, the operations further comprising classifying the plurality of vehicles by comparing the plurality of aligned vehicle shapes to the one or more vehicle profiles.

### Claim 14 (depends on 10)

The system of claim 10, the operations further comprising:
receiving additional laser scan data corresponding to at least one additional vehicle;
extracting, based on the additional laser scan data, at least one additional vehicle shape corresponding to the at least one additional vehicle; and
classifying the at least one additional vehicle by comparing the at least one additional vehicle shape to the one or more vehicle profiles.

### Claim 15 (depends on 10)

The system of claim 10, wherein the plurality of vehicle shapes are two-dimensional shapes.

### Claim 16 (depends on 10)

The system of claim 10, wherein the plurality of vehicle shapes are three-dimensional shapes.

### Claim 17 (depends on 10)

The system of claim 10, the operations further comprising, prior to extracting the plurality of vehicle shapes, replacing missing data in the laser scan data using interpolation based on the missing data's neighbor in the laser scan data.

### Claim 18 (depends on 10)

The system of claim 10, the operations further comprising identifying and extracting data corresponding to vehicles of interest in the laser scan data, wherein extracting, based on the laser scan data, the plurality of vehicle shapes comprises extracting the plurality of vehicle shapes from the extracted data.