Real-time cyclist detection using synthetic training data

A technology for cyclists, composite images, applied in instruments, character and pattern recognition, computer parts, etc., can solve the problem of object size reducing image quality, not suitable for real-time applications, increasing complexity, etc.

Active Publication Date: 2017-05-03
HONDA MOTOR CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This results in large variations in object size and reduced image quality through motion blur and defocus
The increased complexity of cyclist detection compared to pedestrian detection means that most detection systems are not suitable for real-time applications

Method used

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  • Real-time cyclist detection using synthetic training data
  • Real-time cyclist detection using synthetic training data
  • Real-time cyclist detection using synthetic training data

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Embodiment Construction

[0020] Embodiments are now described with reference to the drawings, wherein like reference numerals indicate identical or functionally similar components. Also, in the figures, the leftmost digit of each reference number corresponds to the figure in which that reference number is first used.

[0021] figure 1 is a high-level block diagram illustrating a cyclist detection system 100 in accordance with an embodiment. The cyclist detection system 100 includes a positive training image generation module 105 , a learning module 110 and a detection module 120 . The cyclist detection system 100 may be used in a vehicle to determine the presence (or absence) of a cyclist in the vicinity of the vehicle. As used herein, "cyclist" refers to the combination of a bicycle and its rider.

[0022] The cyclist detection system 100 may be used, for example, in a vehicle to improve the safety of occupants of the vehicle as well as the safety of cyclists sharing the road with the vehicle. W...

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PUM

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Abstract

Each embodiment of the invention generally relates to real-time rider detection by using synthetic training data, and relates to determining the existence of a rider at real-time in detail. The steps are as follows: receiving a target image; classifying the target image by using a linear classifier and determining an error value of the target image. If the error value is no more than a threshold, the classification is output. Or else, if the error value is larger than the threshold, the target is classified by using a nonlinear classifier.

Description

[0001] related application [0002] This application claims the benefit of US Provisional Application No. 61 / 745,225, filed December 21, 2012, which is hereby incorporated by reference in its entirety. technical field [0003] This application relates generally to the field of object detection, and in particular to detecting the presence of cyclists using hierarchical classifiers. Background technique [0004] "Object detection" refers to the task of automatically detecting the presence of objects in video images or still images. For example, a detection system may detect the presence of a person or bicyclist in a still image. As used herein, "cyclist" refers to the combination of a bicycle and its rider. [0005] Object detection can be used, for example, in vehicles (eg, cars) to improve the safety of the vehicle's driver, passengers, cyclists, and anyone else sharing the road with the vehicle. [0006] There are many problems with current object detection systems. On...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00
Inventor B·海斯勒
Owner HONDA MOTOR CO LTD
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