Light-invariant 3D object's pose estimation using color distance transform

Kyriakoulis, Nikolaos; Γαστεράτος, Αντώνιος

doi:10.1109/ist.2010.5548505

Cited by 5 publications

(7 citation statements)

References 22 publications

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“…Marker detection is based on a simple color segmentation by thresholding performed in the HSV (hue, saturation, value) color space because HSV allows robust segmentation of objects that undergo non-uniform levels of illumination intensity, shadows and shading [10,15]. In particular, segmentation based on saturation and hue allows wider color range to be covered and therefore it is less dependent on the lighting conditions within the scene (mainly affecting the V channel).…”

Section: Colored Strip Implementationmentioning

confidence: 99%

Robust Laparoscopic Instruments Tracking Using Colored Strips

Mamone

Viglialoro

Cutolo

et al. 2017

Lecture Notes in Computer Science

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To assist surgeons in the acquisition of the required skills for the proper execution of the laparoscopic procedure, surgical simulators are used.During training with simulators it is useful to provide a surgical performance quantitative evaluation. Recent research works showed that such evaluation can be obtained by tracking the laparoscopic instruments, using only the images provided by the laparoscope and without hindering the surgical scene. In this work the state of the art method is improved so that a robust tracking can run even with the noisy background provided by realistic simulators. The method was validated by comparison with the tracking of a "chess-board" pattern and following tests were performed to check the robustness of the developed algorithm. Despite the noisy environment, the implemented method was found to be able to track the tip of the surgical instrument with a good accuracy compared to the other studies in the literature.

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Section: Colored Strip Implementationmentioning

confidence: 99%

Robust Laparoscopic Instruments Tracking Using Colored Strips

Mamone

Viglialoro

Cutolo

et al. 2017

Lecture Notes in Computer Science

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“…HSV is a human-oriented representation of the distribution of the electromagnetic radiation energy spectrum [44]. HSV enables a sufficiently robust segmentation of objects that undergo non-uniform levels of illumination intensity, shadows, and shading [45,46]. The assumption is that light intensity primarily affects the value (V) channel, whereas the hue (H), and to a lesser extent the saturation (S) channels are less influenced by illumination changes [46].…”

Section: Feature Extraction Stereo Correspondence and Marker Labelingmentioning

confidence: 99%

Robust and Accurate Algorithm for Wearable Stereoscopic Augmented Reality with Three Indistinguishable Markers

et al. 2016

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Abstract:In the context of surgical navigation systems based on augmented reality (AR), the key challenge is to ensure the highest degree of realism in merging computer-generated elements with live views of the surgical scene. This paper presents an algorithm suited for wearable stereoscopic augmented reality video see-through systems for use in a clinical scenario. A video-based tracking solution is proposed that relies on stereo localization of three monochromatic markers rigidly constrained to the scene. A PnP-based optimization step is introduced to refine separately the pose of the two cameras. Video-based tracking methods using monochromatic markers are robust to non-controllable and/or inconsistent lighting conditions. The two-stage camera pose estimation algorithm provides sub-pixel registration accuracy. From a technological and an ergonomic standpoint, the proposed approach represents an effective solution to the implementation of wearable AR-based surgical navigation systems wherever rigid anatomies are involved.

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“…In 2009, Kyriakoulis N [4] used color histogram to extract markers with known geometrical arrangement for pose estimation. Subsequently, in 2010, they isolated the marker using color distance transform to estimate the pose [5]. In 2013, Wang Q Z [6] used splitting technology to detect color information from which the pose is estimated.…”

Section: Introductionmentioning

confidence: 99%

3D Object’s Pose Estimation Based on Colored Markers Information

Gao

Zhang

et al. 2013

AMR

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Pose estimation of 3d object is a hot research in the field of computer vision. This paper presents a novel pose estimation method based on colored markers. To overcome the effect of the luminance and other colors, this method uses the HSV color space and isolates the colors operating only on chromaticity plane where value (V) has no actual effect for identifying the colored regions of interest. The template is then applied on the remaining colors in order to find the center of the region. The pixels which have the same color but are not in the marker area are excluded, since they are considered noisy. The template guarantees the stability and efficiency of the extraction of the feature points. Compared with the CDT algorithm, the proposed method can extract reliable center points, and has higher accuracy in pose estimation for planar rigid objects. At last, experimental results demonstrate the efficiency of the method.

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Light-invariant 3D object's pose estimation using color distance transform

Cited by 5 publications

References 22 publications

Robust Laparoscopic Instruments Tracking Using Colored Strips

Robust Laparoscopic Instruments Tracking Using Colored Strips

Robust and Accurate Algorithm for Wearable Stereoscopic Augmented Reality with Three Indistinguishable Markers

3D Object’s Pose Estimation Based on Colored Markers Information

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