A monocular distance estimation method used in video sequence

Li, Xiaolei; Wang, Lu

doi:10.1109/icinfa.2012.6246836

Cited by 3 publications

(5 citation statements)

References 5 publications

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“…Among these emerged researches, most work assumes the camera pose is fixed [3,6,9,10,[12][13][14]. Some notable exceptions, which have similarity to the present work, are as follows.…”

Section: Related Workmentioning

confidence: 76%

“…(1) Guo et al [15] put forward a parallel constraint method based on the two lane boundaries. (2) Vehicles are equipped with an angle sensor to accurately acquire the pitching angle of the camera in [13,16,17], where the author proposed an improved algorithm in angle calculation by using a function of the angles representing the two parallel lane lines.…”

Section: Related Workmentioning

confidence: 99%

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An Analytical Measuring Rectification Algorithm of Monocular Systems in Dynamic Environment

Wang

2016

Journal of Sensors

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Range estimation is crucial for maintaining a safe distance, in particular for vision navigation and localization. Monocular autonomous vehicles are appropriate for outdoor environment due to their mobility and operability. However, accurate range estimation using vision system is challenging because of the nonholonomic dynamics and susceptibility of vehicles. In this paper, a measuring rectification algorithm for range estimation under shaking conditions is designed. The proposed method focuses on how to estimate range using monocular vision when a shake occurs and the algorithm only requires the pose variations of the camera to be acquired. Simultaneously, it solves the problem of how to assimilate results from different kinds of sensors. To eliminate measuring errors by shakes, we establish a pose-range variation model. Afterwards, the algebraic relation between distance increment and a camera’s poses variation is formulated. The pose variations are presented in the form of roll, pitch, and yaw angle changes to evaluate the pixel coordinate incensement. To demonstrate the superiority of our proposed algorithm, the approach is validated in a laboratory environment using Pioneer 3-DX robots. The experimental results demonstrate that the proposed approach improves in the range accuracy significantly.

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“…Among these emerged researches, most work assumes the camera pose is fixed [3,6,9,10,[12][13][14]. Some notable exceptions, which have similarity to the present work, are as follows.…”

Section: Related Workmentioning

confidence: 76%

Section: Related Workmentioning

confidence: 99%

An Analytical Measuring Rectification Algorithm of Monocular Systems in Dynamic Environment

Wang

2016

Journal of Sensors

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“…However, monocular vision based PCAS technology is cost effective [4], [5]. Recently, intensive research has been carried out to develop algorithms to estimate distances of the target objects (pedestrians or other motor vehicles) from the host vehicle based on monocular vision [6]- [11].…”

Section: Introductionmentioning

confidence: 99%

“…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. However, degradation in accuracy in the estimated values of distances is found at larger distances, such as 50 m from the camera.…”

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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“…There are several works that discusses the application of monocular vision camera. These [4,[11][12] .…”

mentioning

confidence: 99%

The effect of illumination compensation methods with histogram back projection for camshift application

Saleh

Rahiman

2018

J. Fundam and Appl Sci.

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This paper presents the results of a factorial experiment performed to determine the effect of illumination compensation methods with histogram back projection to be used for tracking algorithm continuous adaptive mean used for distance approximation of an object, a precise tracker algorithm is required. This study compared two types of illumination compensation methods us (DOE) in the presence of illumination inconsistency. Based on the results, it was found that selecting two channels as reference in histogram back projection weakens the accuracy of Camshift tracking whereas the combination of both desirable.

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A monocular distance estimation method used in video sequence

Cited by 3 publications

References 5 publications

An Analytical Measuring Rectification Algorithm of Monocular Systems in Dynamic Environment

An Analytical Measuring Rectification Algorithm of Monocular Systems in Dynamic Environment

Monocular vision based distance estimation algorithm for pedestrian collision avoidance systems

The effect of illumination compensation methods with histogram back projection for camshift application

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