# US 2021/0278858 A1 · Method and apparatus for recognizing object

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- Number: US 2021/0278858 A1
- Document ID: US20210278858A1
- Status: Published application
- Kind: A1
- Application number: 17/329,352
- Filed: 2021-05-25
- Published: 2021-09-09
- Earliest claimed: 2017-09-04
- Assignees: Samsung Electronics Co., Ltd.
- Applicants: Samsung Electronics Co., Ltd.
- Inventors: PaulBarom JEON
- Web page: https://patentgrep.com/patent/US20210278858A1

## CPC

- G06V 20/56: exterior to a vehicle by using sensors mounted on the vehicle
- G05D 1/0246: {using a video camera in combination with image processing means}
- G06F 18/2163: {Partitioning the feature space}
- G06F 18/241: relating to the classification model, e.g. parametric or non-parametric approaches
- G06F 18/29: {Graphical models, e.g. Bayesian networks}
- G06T 7/11: Region-based segmentation
- G06V 10/25: Determination of region of interest [ROI] or a volume of interest [VOI]
- G06V 10/255: {Detecting or recognising potential candidate objects based on visual cues, e.g. shapes}
- G06V 10/454: {Integrating the filters into a hierarchical structure, e.g. convolutional neural networks [CNN]}
- G06V 10/82: using neural networks
- G06T 2207/20084: Artificial neural networks [ANN]
- G06T 2207/30261: Obstacle
- 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
- G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G05D: SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL

## Abstract

A method and apparatus for recognizing an object are provided, including extracting a feature from an input image and generating a feature map in a neural network. In parallel with the generating of the feature map, a region of interest (ROI) corresponding to an object of interest is extracted from the input image, and a number of object candidate regions used to detect the object of interest is determined based on a size of the ROI. The object of interest is recognized from the ROI based on the number of object candidate regions in the neural network.

## Claims

### Claim 1

An object recognition apparatus comprising:
a processor configured to generate a feature map by extracting a feature from an input image using a neural network, to extract, in parallel with a generation of the feature map, a region of interest (ROI) corresponding to an object of interest from the input image, and to determine, based on a size of the ROI and a size of the input image, a number of object candidate regions used to detect the object of interest,
wherein the neural network is further configured to recognize the object of interest from the ROI based on the number of object candidate regions.

### Claim 2 (depends on 1)

The object recognition apparatus of claim 1, wherein the processor is further configured to calculate a ratio of the size of the ROI to the size of the input image and to determine the number of object candidate regions based on the ratio.

### Claim 3 (depends on 1)

The object recognition apparatus of claim 1, wherein the processor is further configured to determine positions of the object candidate regions on the feature map, and to recognize the object of interest from the ROI based on the positions of the object candidate regions.

### Claim 4 (depends on 1)

The object recognition apparatus of claim 1, wherein the processor is further configured to extract the ROI based on any one or any combination of a training-based scene segmentation algorithm and an image processing algorithm.

### Claim 5 (depends on 1)

The object recognition apparatus of claim 1, wherein the neural network comprises a region-based convolutional neural network (R-CNN) comprising a region proposal network (RPN) and a detection network.

### Claim 6 (depends on 1)

The object recognition apparatus of claim 1, wherein the processor is further configured to determine a control parameter to control a speed of a vehicle and a traveling direction of the vehicle based on a result of the recognizing, and to control a movement of the vehicle using the control parameter.

### Claim 7

An object recognition apparatus comprising:
a processor configured to extract a region of interest (ROI) corresponding to an object of interest from the input image, to determine, based on a size of the ROI and a size of the input image, a number of object candidate regions, and to detect the object of interest from the ROI based on the number of object candidate regions using a neural network.

### Claim 8 (depends on 7)

The object recognition apparatus of claim 7, wherein the object of interest comprises any one or any combination of a road, a vehicle, a human, an animal, a plant, and a building.

### Claim 9 (depends on 7)

The object recognition apparatus of claim 7, wherein the ROI comprises a region corresponding to one or any combination of a road, a vehicle, a human, an animal, a plant, and a building.