Monocular ego-motion estimation with a compact omnidirectional camera

Stürzl, Wolfgang; Burschka, Darius; Suppa, Michael

doi:10.1109/iros.2010.5649970

Cited by 2 publications

(2 citation statements)

References 27 publications

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“…There are other similar algorithms in the professional literature [27,28,29,30,31,32], which have even been adapted for to operate with a monocular [30] or an omnidirectional video camera [33,34,35,36], and recently, extended to Simultaneous Localization and Mapping (SLAM) [37,38]. Refer to [39,40] for a comprehensive tutorial on visual odometry.…”

Section: Introductionmentioning

confidence: 99%

Experimental Results of Testing a Direct Monocular Visual Odometry Algorithm Outdoors on Flat Terrain under Severe Global Illumination Changes for Planetary Exploration Rovers

Martínez¹

2018

CyS

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We present the experimental results obtained by testing a monocular visual odometry algorithm on a real robotic platform outdoors, on flat terrain, and under severe changes of global illumination. The algorithm was proposed as an alternative to the long-established feature based stereo visual odometry algorithms. The rover's 3D position is computed by integrating the frame to frame rover's 3D motion over time. The frames are taken by a single video camera rigidly attached to the rover looking to one side tilted downwards to the planet's surface. The frame to frame rover's 3D motion is directly estimated by maximizing the likelihood function of the intensity differences at key observation points, without establishing correspondences between features or solving the optical flow as an intermediate step, just directly evaluating the frame to frame intensity differences measured at key observation points. The key observation points are image points with high linear intensity gradients. Comparing the results with the corresponding ground truth data, which was obtained by using a robotic theodolite with a laser range sensor, we concluded that the algorithm is able to deliver the rover's position in average of 0.06 seconds after an image has been captured and with an average absolute position error of 0.9% of distance traveled. These results are quite similar to those reported in scientific literature for traditional feature based stereo visual odometry algorithms, which were successfully used in real rovers here on Earth and on Mars. We believe that they represent an important step towards the validation of the algorithm and make us think that it may be an excellent tool for any autonomous robotic platform, since it could be very helpful in situations in which the traditional feature based visual odometry algorithms have failed. It may also be an excellent candidate to be merged with other positioning algorithms and/or sensors.

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Section: Introductionmentioning

confidence: 99%

Experimental Results of Testing a Direct Monocular Visual Odometry Algorithm Outdoors on Flat Terrain under Severe Global Illumination Changes for Planetary Exploration Rovers

Martínez¹

2018

CyS

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“…Owing to the highly articulated characteristic of a pedestrian, this method is not ideal to be used for monocular ranging in PCAS. In [10], the authors present a monocular ego motion estimation algorithm that is iterative. In [11]- [13], the authors propose techniques based on thin lens camera model and polynomial based interpolation.…”

Section: Introductionmentioning

confidence: 99%

Monocular vision based distance estimation algorithm for pedestrian collision avoidance systems

Awasthi¹,

Singh²,

Roh³

2014

2014 5th International Conference - Confluence the Next Generation Information Technology Summit (Confluence)

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this paper presents a novel and effective distance estimation algorithm based on monocular vision for pedestrian collision avoidance systems (PCAS). Vehicle -camera geometry and intrinsic parameters of camera are used to estimate the distances of pedestrians detected in front of the ego vehicle. An innovative method to estimate the pitch angle for the camera is provided in the proposed solution. The advantage of the intrinsic parameters based method is that the algorithm is computationally efficient to meet the real time requirements of the system. In addition to this, it takes into account the system requirements, in the sense, that instead of estimating point to point distance between the camera and the target pedestrian, the vertical distance is estimated with the help of vertical and pitch angles. Practical issues like pixel density per distance value shrinkage at higher distances, lens distortion and jitters are addressed and solutions to them are provided. In multiple experimental tests under real world driving conditions, it has been confirmed that the proposed solution works effectively with a minimal percentage mean error rate.

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Monocular ego-motion estimation with a compact omnidirectional camera

Cited by 2 publications

References 27 publications

Experimental Results of Testing a Direct Monocular Visual Odometry Algorithm Outdoors on Flat Terrain under Severe Global Illumination Changes for Planetary Exploration Rovers

Experimental Results of Testing a Direct Monocular Visual Odometry Algorithm Outdoors on Flat Terrain under Severe Global Illumination Changes for Planetary Exploration Rovers

Monocular vision based distance estimation algorithm for pedestrian collision avoidance systems

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