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Pedestrian detection is one of the most important techniques for surveillance applications. This paper proposes an effective method for pedestrian detection in low-contrast images. The main characteristic of the proposed method is a two-stage moving object extraction. In the first stage, the watershed algorithm is used to extract multiple regions of moving objects. In the second stage, a novel criterion...
Road segmentation is an essential functionality for supporting advanced driver assistance systems (ADAS) such as road following and vehicle and pedestrian detection. Significant efforts have been made in order to solve this task using vision-based techniques. The major challenge is to deal with lighting variations and the presence of objects on the road surface. In this paper, we propose a new road...
Road detection is a vital task for the development of autonomous vehicles. The knowledge of the free road surface ahead of the target vehicle can be used for autonomous driving, road departure warning, as well as to support advanced driver assistance systems like vehicle or pedestrian detection. Using vision to detect the road has several advantages in front of other sensors: richness of features,...
Accurately counting people waiting at bus stops is essential for automated bus fleet scheduling and dispatch. Estimating the passenger demand in regular open bus stops is a nontrivial problem because of the varying conditions, such as illumination, crowdedness, people poses, to name a few. This paper presents a simple, but very effective approach to estimate the passenger count using people density...
Human-robot interaction approaches like face detection, face recognition, pedestrian detection are widely known in robotics field; however often they lead to performance problems. Additionally, false positive and false negative problems are commonly associated to bad illumination and strong featured images. Moreover background segmentation approaches are frequently used to solve this problem on static...
Interactive mobile robots require object/subject detection in very visually complex environments. In the field of computer vision, specially when applied to robotics, several approaches like face detection, face recognition and pedestrian detection often have to deal with issues associated to bad illumination and strong featured background. These issues imply lack of performance because human detection...
Pedestrian detection is one of the most important components in driver-assistance systems. In this paper, we propose a monocular vision system for real-time pedestrian detection and tracking during nighttime driving with a near-infrared (NIR) camera. Three modules (region-of-interest (ROI) generation, object classification, and tracking) are integrated in a cascade, and each utilizes complementary...
In this paper, we present a system for pedestrian detection involving scenes captured by mobile bus surveillance cameras in busy city streets. Our approach integrates scene localization, foreground and background separation, and pedestrian detection modules into a unified detection framework. The scene localization module performs a two stage clustering of the video data. In the first stage, SIFT...
Pedestrian detection is particularly challenging, comparing with other targets in the domain of object detection, especially for night driving just with a normal camera. In this paper we combine two probabilistic templates based classifiers for elaborate pedestrian detection: the binary probabilistic template based classifier (BPTC) as the first layer to reject most of non-pedestrians by the features...
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