Pedestrian Detection Based on Motion Compensation and HOG/SVM Classifier

Xu, Fen; Xu, Feng

doi:10.1109/ihmsc.2013.227

Cited by 6 publications

(2 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For feature extraction, techniques such as Histogram of Oriented Gradients [93][94][95][96][97][98][99][100], Local Binary Pattern [101][102][103][104][105][106][107], Deformable Part Model [108][109][110][111][112][113], and Aggregate Channel Feature (ACF) [114][115][116][117][118] are included. On the other hand, methods such as Support Vector Machine (SVM) [94,105,[119][120][121][122], Decision Tree [123][124][125][126], Random Forest (RF) [127][128][129][130][131][132] and Ada-Boost [81,119,133,134] are used for the classification process.…”

Section: Object Detection and Classificationmentioning

confidence: 99%

Vulnerable Road Users and Connected Autonomous Vehicles Interaction: A Survey

Reyes-Muñoz

Ibáñez

2022

Sensors

View full text Add to dashboard Cite

There is a group of users within the vehicular traffic ecosystem known as Vulnerable Road Users (VRUs). VRUs include pedestrians, cyclists, motorcyclists, among others. On the other hand, connected autonomous vehicles (CAVs) are a set of technologies that combines, on the one hand, communication technologies to stay always ubiquitous connected, and on the other hand, automated technologies to assist or replace the human driver during the driving process. Autonomous vehicles are being visualized as a viable alternative to solve road accidents providing a general safe environment for all the users on the road specifically to the most vulnerable. One of the problems facing autonomous vehicles is to generate mechanisms that facilitate their integration not only within the mobility environment, but also into the road society in a safe and efficient way. In this paper, we analyze and discuss how this integration can take place, reviewing the work that has been developed in recent years in each of the stages of the vehicle-human interaction, analyzing the challenges of vulnerable users and proposing solutions that contribute to solving these challenges.

show abstract

Section: Object Detection and Classificationmentioning

confidence: 99%

Vulnerable Road Users and Connected Autonomous Vehicles Interaction: A Survey

Reyes-Muñoz

Ibáñez

2022

Sensors

View full text Add to dashboard Cite

show abstract

“…A set of ground sensors are employed to detect intruders in red zone where false alarm reate is very high due to limitations in computation techniques [8]. Researchers toiled to identify motion of human through wavelet based target detection method with fast execution time and low memory requirements.…”

Section: Related Workmentioning

confidence: 99%

Server Based Wireless Motion Detection System Using PIR Sensor

Timande¹

2013

IJNPME

View full text Add to dashboard Cite

Detecting human movement plays a vital in this industrial era where it can be effectively used in industrial sectors dealing with reactors and boilers. A server based automated system that allows only the authorized persons to enter into the hazardous zone that will avoid misguiding of the system by unknown persons. In this research article, a server based motion detection module involving PIR sensor and GSM is proposed. Here we use two modules one is digital image processing and another one is embedded system. It is used to detect any obstacle in within its field. Once obstacle will be detected camera will be on. Camera captured an upcoming image and check whether it is a human or animal, if it is a human it will compare with input database images, then easily find unauthorized person.

show abstract