Centralized fusion for fast people detection in dense environment

Gate, Gwennael; Breheret, Amaury; Nashashibi, Fawzi

doi:10.1109/robot.2009.5152645

Cited by 27 publications

(25 citation statements)

References 16 publications

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“…Hence, these sensors have been used to detect and track pedestrians [10], [11]. In [11], the authors defined various scores for detection, recognition and tracking of pedestrians in laser and vision data in order to distinguish pedestrians and non pedestrians, showing the feasibility of a fast sensor based pedestrian detection algorithm in a complex urban environment. However, this approach does not consider scenarios, where pedestrians might be hidden behind an obstacle.…”

Section: Related Workmentioning

confidence: 99%

Study on Perception and Communication Systems for Safety of Vulnerable Road Users

Merdrignac¹,

Shagdar²,

Jemaa³

et al. 2015

2015 IEEE 18th International Conference on Intelligent Transportation Systems

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The existing R&D efforts for protecting vulnerable road users (VRU) are mainly based on perception techniques, which aim to detect VRUs utilizing vehicle embedded sensors. The efficiency of such a technique is largely affected by the sensor's visibility condition. Vehicle-to-Pedestrian (V2P) communication can also contribute to the VRU safety by allowing vehicles and pedestrians to exchange information. This solution is, however, largely affected by the reliability of the exchanged information, which most generally is the GPS data. Since perception and communication have complementary features, we can expect that a combination of such approaches can be a solution to the VRU safety. This is the motivation of the current work. We develop theoretical models to present the characteristics of perception and communications systems. Experimental studies are conducted to compare the performances of these techniques in real-world environments. Our results show that the perception system reliably detects pedestrians and other objects within 50 m of range in the line-of-sight (LOS) condition. In contrast, the V2P communication coverage is approximately 340 and 200 meters in LOS and non-LOS (NLOS) conditions, respectively. However, the communication-based system fails to correctly position the VRU w.r.t the vehicle, preventing the system from meeting the safety requirement. Finally, we propose a cooperative system that combines the outputs of the communication and perception systems.

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Section: Related Workmentioning

confidence: 99%

Study on Perception and Communication Systems for Safety of Vulnerable Road Users

Merdrignac¹,

Shagdar²,

Jemaa³

et al. 2015

2015 IEEE 18th International Conference on Intelligent Transportation Systems

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“…Active safety systems consist of sensors to observe the surrounding environment of the vehicle, applications to detect probable hazardous situations, and actuators to respond to them appropriately. A vision-based active safety mechanism for pedestrian detection is described in [9], in which a rangefinder is utilized to detect pedestrians. A similar approach is adopted in [10] which used a camera and laser scanner for pedestrian detection.…”

Section: Introductionmentioning

confidence: 99%

Implementation and Evaluation of a Cooperative Vehicle-to-Pedestrian Safety Application

Tahmasbi-Sarvestani

Mahjoub

Fallah

et al. 2017

IEEE Intell. Transport. Syst. Mag.

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While the development of Vehicle-to-Vehicle (V2V) safety applications based on Dedicated Short-Range Communications (DSRC) has been extensively undergoing standardization for more than a decade, such applications are extremely missing for Vulnerable Road Users (VRUs). Nonexistence of collaborative systems between VRUs and vehicles was the main reason for this lack of attention. Recent developments in Wi-Fi Direct and DSRC-enabled smartphones are changing this perspective. Leveraging the existing V2V platforms, we propose a new framework using a DSRC-enabled smartphone to extend safety benefits to VRUs. The interoperability of applications between vehicles and portable DSRC-enabled devices is achieved through the SAE J2735 Personal Safety Message (PSM). However, considering the fact that VRU movement dynamics, response times, and crash scenarios are fundamentally different from vehicles, a specific framework should be designed for VRU safety applications to study their performance. In this article, we first propose an endto-end Vehicle-to-Pedestrian (V2P) framework to provide situational awareness and hazard detection based on the most common and injury-prone crash scenarios. The details of our VRU safety module, including target classification and collision detection algorithms, are explained next. Furthermore, we propose and evaluate a mitigating solution for congestion and power consumption issues in such systems. Finally, the whole system is implemented and analyzed for realistic crash scenarios.

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“…Thus, fusion systems using LIDAR and a camera have also been developed for pedestrian detection. Gate et al [10] combined multilayer LIDAR with a single camera. Pedestrian candidates are extracted from 2D range data measured by LIDAR, and vision-based pattern recognition verifies only those extracted candidates.…”

Section: Introductionmentioning

confidence: 99%

Reliable pedestrian recognition combining high-definition LIDAR and vision data

Kidono

Naito

Miura

2012

2012 15th International IEEE Conference on Intelligent Transportation Systems

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Pedestrian recognition is one of the key technologies for advanced driver assistance systems and autonomous driving systems. The present paper proposes a fusion system for reliable pedestrian recognition using high-definition LIDAR and a vision sensor to achieve high performance under various conditions. Pedestrian candidates are extracted from two sensors in parallel by support vector machine-based classifiers. In particular, the region of interest in the image processing is set based on information about objects derived from the LIDAR processing in order to reduce false positives as well as the computational burden. All candidates are integrated by their likelihood, as calculated from their classification scores, using multiple thresholds according to the detection condition of the target in two sensors. A quantitative evaluation in a road environment confirms the effectiveness of the proposed system.

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Centralized fusion for fast people detection in dense environment

Cited by 27 publications

References 16 publications

Study on Perception and Communication Systems for Safety of Vulnerable Road Users

Study on Perception and Communication Systems for Safety of Vulnerable Road Users

Implementation and Evaluation of a Cooperative Vehicle-to-Pedestrian Safety Application

Reliable pedestrian recognition combining high-definition LIDAR and vision data

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