Free space determination for parking slots using a 3D PMD sensor

Scheunert, U.; Fardi, B.; Mattern, Norman; Wanielik, Gerd; Keppeler, N.

doi:10.1109/ivs.2007.4290107

Cited by 22 publications

(14 citation statements)

References 3 publications

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“…PMD sensor allows referring to a large number of spatial point measurements detailed representing cuts of the observed scene [6]. So we moved onto Infrastructure based method.…”

Section: Literature Reviewmentioning

confidence: 99%

Review on Automatic Car Parking Indicator System

Amit¹

2015

IJRITCC

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Abstract-Parking is costly and limited in almost every major city in the world. An Automatic car parking systems for meeting near term parking demand are needed. There is need to develop a vacant parking slot detection and tracking system. Around view monitor (AVM) image sequence makes it possible with 360-degree scene Bird's eye view camera. Around view monitor (AVM) captures the image sequence and on combining of each images empty slot is detected. The Ultrasonic sensor is useful to determine the adjacent vehicle. Hierarchical tree structure based parking slot marking method is used to recognize the parking slot marking. After combining sequentially detected parking slot, empty parking slot is recognized and the driver has to select one of the empty parking slots and drive into it.Key Words-Around View Monitor (AVM), Ultrasonic sensor, The Hierarchical tree structure of the parking slot marking, parking slot marking detection and tracking, recognition of the empty parking slot.

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“…PMD sensor allows referring to a large number of spatial point measurements detailed representing cuts of the observed scene [6]. So we moved onto Infrastructure based method.…”

Section: Literature Reviewmentioning

confidence: 99%

Review on Automatic Car Parking Indicator System

Amit¹

2015

IJRITCC

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“…In its basic form the occupancy grid [2] is used to represent occupied space and to distinguish it from empty areas. In [3] an occupancy grid based approach is used for parking slot free space detection. Occupancy grids are furthermore often used for mapping purposes [4].…”

Section: Related Workmentioning

confidence: 99%

Advanced occupancy grid techniques for lidar based object detection and tracking

Richter

Lindner

Wanielik

et al. 2009

2009 12th International IEEE Conference on Intelligent Transportation Systems

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The robust and reliable detection of objects in the surrounding of a vehicle is an important prerequisite for collision avoidance and collision mitigation systems. In this paper, an ego-motion compensated tracking approach is presented which uses extended occupancy grid methods for both detection and tracking of objects observed by lidar. The approach is able to estimate the velocity and direction of moving objects as well as to distinguish between moving and stationary objects. Additionally, an approach for drastically reducing the computational effort is presented.

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“…This is the most widely used approach as it can be implemented using various range-finding sensors, such as ultrasonic sensors [9][10][11][12][13][14][15], laser scanners [16][17][18], short-range radars [19][20][21], structured light [22], depth cameras [23], stereo cameras [24][25][26][27][28][29], etc. However, the free-space-based approach has an inherent drawback in that it cannot find free spaces when there is no adjacent vehicles and its accuracy depends on the positions and poses of adjacent vehicles.…”

Section: Introductionmentioning

confidence: 99%

Vision-Based Parking-Slot Detection: A Benchmark and A Learning-Based Approach

Zhang

Huang

et al. 2018

Symmetry

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Recent years have witnessed a growing interest in developing automatic parking systems in the field of intelligent vehicles. However, how to effectively and efficiently locating parking-slots using a vision-based system is still an unresolved issue. Even more seriously, there is no publicly available labeled benchmark dataset for tuning and testing parking-slot detection algorithms. In this paper, we attempt to fill the above-mentioned research gaps to some extent and our contributions are twofold. Firstly, to facilitate the study of vision-based parking-slot detection, a large-scale parking-slot image database is established. This database comprises 8600 surround-view images collected from typical indoor and outdoor parking sites. For each image in this database, the marking-points and parking-slots are carefully labeled. Such a database can serve as a benchmark to design and validate parking-slot detection algorithms. Secondly, a learning-based parking-slot detection approach, namely PSD L , is proposed. Using PSD L , given a surround-view image, the marking-points will be detected first and then the valid parking-slots can be inferred. The efficacy and efficiency of PSD L have been corroborated on our database. It is expected that PSD L can serve as a baseline when the other researchers develop more sophisticated methods.

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Free space determination for parking slots using a 3D PMD sensor

Cited by 22 publications

References 3 publications

Review on Automatic Car Parking Indicator System

Review on Automatic Car Parking Indicator System

Advanced occupancy grid techniques for lidar based object detection and tracking

Vision-Based Parking-Slot Detection: A Benchmark and A Learning-Based Approach

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