Vision-based pedestrian detection -reliable pedestrian candidate detection by combining IPM and a 1D profile

Ma, Guanglin; Park, Su-Birm; Miiller-Schneiders, S.; Ioffe, A.; Kummert, Anton

doi:10.1109/itsc.2007.4357628

Cited by 15 publications

(11 citation statements)

References 13 publications

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“…Simond and Parent 34 combined the IPT with the computation of the ground plane super-homography to discriminate obstacles from road in an autonomous guided vehicle application. Ma et al 22 presented an automatic pedestrian detection algorithm based on IPT for self-guided vehicles. The system predicted new frames assuming that all image points laid on the floor.…”

Section: Related Workmentioning

confidence: 99%

A monocular mobile robot reactive navigation approach based on the inverse perspective transformation

Bonin‐Font¹,

Burguera²,

Ortiz³

et al. 2012

Robotica

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This paper presents an approach to visual obstacle avoidance and reactive robot navigation for outdoor and indoor environments. The obstacle detection algorithm includes an image feature tracking procedure followed by a feature classification process based on the IPT (Inverse Perspective Transformation). The classifier discriminates obstacle points from ground points. Obstacle features permit to draw out the obstacle boundaries which are used to construct a local and qualitative polar occupancy grid, analogously to a visual sonar. The navigation task is completed with a robocentric localization algorithm to compute the robot pose by means of an EKF (Extended Kalman Filter). The filter integrates the world coordinates of the ground points and the robot position in its state vector. The visual pose estimation process is intended to correct possible drifts on the dead-reckoning data provided by the proprioceptive robot sensors. The experiments, conducted indoors and outdoors, illustrate the range of scenarios where our proposal has proved to be useful, and show, both qualitatively and quantitatively, the benefits it provides.

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Section: Related Workmentioning

confidence: 99%

A monocular mobile robot reactive navigation approach based on the inverse perspective transformation

Bonin‐Font¹,

Burguera²,

Ortiz³

et al. 2012

Robotica

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“…Shu and Tan (Shu & Tan, 2004) also employed the IPM to detect road lanes for self-guided vehicles. Ma et al (Ma et al, 2007) presented an automatic pedestrian detection algorithm based on IPM for self-guided vehicles. The system predicted new frames assuming that all image points laid on the floor.…”

Section: Inverse Perspective Transformation-based Obstacle Detectionmentioning

confidence: 99%

A Visual Navigation Strategy Based on Inverse Perspective Transformation

Bonin‐Font¹,

Ortiz²,

Oliver³

2010

Robot Vision

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“…Pedestrian candidate detections are generated by searching for strong vertical edges in a region of interest using the Inverse Perspective Matching profile [6]. The vertical bottom point of the object is found by conducting a footpoint search on the image.…”

Section: The Pedestrian Recognition Systemmentioning

confidence: 99%

The unscented Kalman filter for pedestrian tracking from a moving host

Meuter

Iurgel

Park

et al. 2008

2008 IEEE Intelligent Vehicles Symposium

Self Cite

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In this paper we present a time-efficient estimation framework for camera-based pedestrian tracking from a moving host car using a monocular camera. An image processing system processes the camera output to find the location of objects of interest in each frame. The position and sensor information about the host translation and rotation are passed to a tracking module. The module uses the position of the detected object's foot point as measurement input and connects them over time to estimate the movement of the objects of interest in order to reduce noise and single frame failures in the detection process. We have developed a new method to estimate the target movement which takes into account the host movement and allows to exploit prior information about the intrinsic and extrinsic camera parameters. The basic idea is to assume that host and target movements can be modelled as 2-dimensional movements on a flat ground-plane. Our developed motion model is based on this assumption and includes host motion as well as the target ego motion. A measurement is modelled as a perspective projection of a point on the groundplane to the image plane. The motion and the measurement model are combined by an Unscented Kalman filter. This filter is relatively new and has not been applied for pedestrian tracking before. Finally, we present a new logical initialization strategy for the selected filter, a part that is left out by most other publications. First results indicate that our approach gives good tracking results and allows to track pedestrians from a moving host in real time.

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Vision-based pedestrian detection -reliable pedestrian candidate detection by combining IPM and a 1D profile

Cited by 15 publications

References 13 publications

A monocular mobile robot reactive navigation approach based on the inverse perspective transformation

A monocular mobile robot reactive navigation approach based on the inverse perspective transformation

A Visual Navigation Strategy Based on Inverse Perspective Transformation

The unscented Kalman filter for pedestrian tracking from a moving host

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