A single camera based rear obstacle detection system

Abstract

This paper presents a rear obstacle detection system by using a single rear view camera. The system can detect various static and moving obstacles behind the cars. An efficient hierarchical detecting strategy is used to achieve high detection rate and low false positives. The temporal Inverse perspective mapping difference image based coarse detection is used to estimate whether there are obstacles in the predetermined warning area at first stage. Then a novel integral image based segmentation algorithm is developed for fine obstacle segmentation. Finally, the blob analysis is utilized for obstacle representation and verification. Our system achieves 94.2% detection rate and 16% false positives rate on 125 challenging video sequences. The average processing speed of the system is 25fps on a standard laptop.

An intelligent depth-based obstacle detection system for visually-impaired aid applications

“…Our system aims to assist the visually-impaired in obstacle detection for safety. Compared with previous works [5] [6] [7], which focus on automotive or robot applications, with assumptions of fix height of camera positions, the pro posed method enables free viewpoint of camera moving, which is more reasonable and further meet the specification of a head-mounted visually-impaired electronic aids. With analysis of different depth layers and object proprieties in the depth map, obstacles can be correctly detected and the corresponding distances from the user can be estimated.…”

“…However, it could only be used in environments with few obstacles because the saliency map must be constructed with coherent characteristics. Zhang Yankun introduced an obstacle detection approach by using a single view image [5]. Based on edge detection for object segmentation, the assumption of the work is that the road surface is a plane without texture.…”

An Object Detection and Identification System for a Mobile Robot Control

“…Different types of sensors are used for obstacle detection [1][2][3][4][5][6][7][8][9][10][11][12][13][14]. Especially, LiDAR (Light Detection and Ranging) is used extensively in both indoor and outdoor applications [7].…”

“…In this kind of systems, images captured from one or more cameras are processed by a computer (or microprocessor-based controller) which is located inside or outside of the mobile robot [1]. Various operations are performed on processed images to detect objects and according to results robot trajectory is re-determined and calculated by controller [7][8][9][10][11][12][13][14]. In general, this technique which uses a single camera provides significant cost advantages.…”

An Obstacle Classification Method Using Multi-feature Comparison Based on 2D LIDAR Database

“…VISION is widely used for obstacle recognition and classification for autonomous vehicle because of its ability to provide information about obstacle types, which cannot be classified by LIDAR [8]. Nevertheless, unlike LIDAR, it has the weak point of having difficulty in providing information about distance between sensor and obstacle, and also in securing fast processing speed required for autonomous vehicle because of relatively larger amount of calculation [9].…”