An improved feature matching technique for stereo vision applications with the use of self-organizing map

Sharma, Kajal; Kim, Sung Gaun; Singh, Manu Pratap

doi:10.1007/s12541-012-0179-z

Cited by 13 publications

(14 citation statements)

References 22 publications

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“…Bumblebee stereo vision camera [9,10] The bumblebee stereo camera generates dense 3D maps, but it results in less accurate maps. The cost of the camera is high.…”

Section: Sensing Methods and Feature-based Algorithms Observationsmentioning

confidence: 99%

“…In addition, it uses slope sensors and incurs a high cost to implement the data. Another range of sensor-based algorithms has been proposed by researchers to design vision applications, including the monocular camera [7], the stereo vision bumblebee camera [9][10][11], and the Microsoft Kinect camera [12,13].…”

Section: Related Workmentioning

confidence: 99%

“…A trinocular camera was used to capture 3D data with three cameras [15], which is an advancement over the stereo camera for searching pixels in the corresponding different scene images. Another method using the bumblebee stereo camera was proposed [9,10] to obtain 3D scene information. It obtains pixel correspondence between left and right images, which is used to generate a disparity map.…”

Section: Related Workmentioning

confidence: 99%

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Mobile Robot Path Finding Using Invariant Landmarks

Sharma¹

2016

IEIE Transactions on Smart Processing and Computing

Self Cite

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This paper proposes a new path-finding scheme using viewpoint-invariant landmarks. The scheme introduces the concept of landmark detection in images captured with a vision sensor attached to a mobile robot, and provides landmark clues to determine a path. Experiment results show that the scheme efficiently detects landmarks with changes in scenes due to the robot's movement. The scheme accurately detects landmarks and reduces the overall landmark computation cost. The robot moves in the room to capture different images. It can efficiently detect landmarks in the room from different viewpoints of each scene. The outcome of the proposed scheme results in accurate and obstacle-free path estimation.

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“…Bumblebee stereo vision camera [9,10] The bumblebee stereo camera generates dense 3D maps, but it results in less accurate maps. The cost of the camera is high.…”

Section: Sensing Methods and Feature-based Algorithms Observationsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Mobile Robot Path Finding Using Invariant Landmarks

Sharma¹

2016

IEIE Transactions on Smart Processing and Computing

Self Cite

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“…For stereo matching approaches based on features, the common features are Scale Invariant Feature Transform (SIFT) features and geometric features. In order to improve the efficiency of the stereo matching of high-speed automobile navigation, Sharma et al combined SIFT features with maps before being stored in the database [4,5]. Joglekar, et al reported relevant parameters of neural networks based on rigorous SIFT matching, and achieved denser stereo matching with the neural networks based on Bayesian decision [6].…”

Section: Introductionmentioning

confidence: 99%

A study of stereo microscope measurements based on interpolated feature matching

Wang

Jiang

et al. 2015

BME

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Abstract. Recently, digital stereo microscopes have been becoming increasingly popular in fields such as biomedicine and biotechnology. As such, being able to precisely match left/right feature pairs is critical, which is an important step in stereo matching. We hereby propose a dynamic interpolation method that combines two dimensional calibration and depth information to achieve stereo matching. In this experiment, we obtained the original scale-invariant feature transform feature point pairs and selected a pair of matching units. Based on the selected pair of matching elements and interpolated feature points shown in the left view of stereo microscope image, the dynamically interpolated feature points in the right view were developed to perform stereo measurements. The experimental results revealed that the proposed method can realize stereo microscopic measurements; results with high reliability can be achieved with a large quantity of matching elements.

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“…SIFT is widely applied by many researchers for stereovision in various situations [7][8][9][10]. However, in the stereovision system, there is no obvious rotation and viewpoint changes between two images captured by two cameras, so we propose a SIFT-based fast stereovision measurement algorithm which generates descriptors by using the pixel values in the block neighbourhood of the SIFT keypoints.…”

Section: Introductionmentioning

confidence: 99%

A fast stereovision measurement algorithm based on SIFT keypoints for mobile robot

Song

Xiao

et al. 2013

2013 IEEE International Conference on Mechatronics and Automation

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When a robot moves independently, it needs to localize itself and avoid obstacles. In order to enable the robot to obtain the depths of surrounding objects, a fast stereovision measurement algorithm based on SIFT keypoints is proposed and implemented on an embedded image processing board based on DSP and FPGA. The calculation of the keypoint descriptor is simplified by directly using the pixel values in the block neighborhood of a keypoint, resulting in an improvement in realtime performance. In order to guarantee the accuracy of searching for the matching points, a two-pass searching strategy is employed, that is, to choose a point in the left image and search the candidate point in the right image, then determine the correspondence by searching the matching point in the left image again. Moreover, for improving the precision of the measurement results, a quadratic polynomial is introduced to compensate the measurement results. Measurement results and comparison of different methods demonstrate the effectiveness of the proposed algorithm. In addition, the measurement system is applied to a mobile robot platform, and the experiment results validate that the system can satisfy the demand of robot applications.

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An improved feature matching technique for stereo vision applications with the use of self-organizing map

Cited by 13 publications

References 22 publications

Mobile Robot Path Finding Using Invariant Landmarks

Mobile Robot Path Finding Using Invariant Landmarks

A study of stereo microscope measurements based on interpolated feature matching

A fast stereovision measurement algorithm based on SIFT keypoints for mobile robot

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