Integrating Visual and Geometric Consistency for Pose Estimation

Background: Use of the interrupted coronary anastomosis has largely been abandoned in favor of the more rapid continuous suturing technique. The Coalescent U-CLIP anastomotic device allows the surgeon to create an interrupted distal anastomosis in the same amount of time that it would take to create a continuous anastomosis. This acute bovine study examined the effect of the anastomotic technique on blood flow and vessel wall function. Methods: End-to-side coronary anastomoses were created in an open chest bovine model using the left and right internal thoracic arteries and the left anterior descending coronary artery. All other variables except suturing technique were carefully controlled. In each animal, one anastomosis was completed using a continuous suturing technique and the other was performed in an interrupted fashion using the Coalescent U-CLIP anastomotic device. Volumetric flow curves through each graft were analyzed using key indicators of anastomotic quality, and anastomotic compliance was evaluated using intravascular ultrasound. Luminal castings were created of each vessel to examine the interior surface of each anastomosis for constrictions and deformities. Results: The interrupted anastomoses created with the Coalescent U-CLIP anastomotic device showed significant differences with respect to anastomotic compliance, pulsatility index, peak flow, and percentage of diastolic flow. The cross-sectional area and degree of luminal deformity were also different for the two suturing techniques. Conclusions: In this acute bovine model, interrupted coronary anastomoses demonstrated superior geometric consistency and greater physiologic compliance than did continuously sutured anastomoses. The interrupted anastomosis also caused fewer disturbances to the flow waveform, behaving similarly to a normal vessel wall. The combination of these effects may influence both acute and long-term patency of the coronary bypass grafts.

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Model-Based Human Pose Estimation and Its Analysis Using Hausdorff Matching

TECHART Journal of Arts and Imaging Science ◽

10.15323/techart.2015.05.2.2.51 ◽

2015 ◽

Vol 2 (2) ◽

pp. 51 ◽

Cited By ~ 1

Author(s):

Vivek Maik ◽

Jinho Park ◽

Daehee Kim ◽

Joonki Paik

Keyword(s):

Pose Estimation ◽

Human Pose Estimation ◽

Model Based ◽

Its Analysis ◽

Human Pose

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Pose Estimation for Non-cooperative Spacecraft based on Deep Learning

2020 39th Chinese Control Conference (CCC) ◽

10.23919/ccc50068.2020.9189253 ◽

2020 ◽

Author(s):

Wenxiu Huan ◽

Mingmin Liu ◽

Qinglei Hu

Keyword(s):

Deep Learning ◽

Pose Estimation

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3D Object Recognition and Relative Localization using a 3D sensor Embedded on a Mobile Robot

10.31237/osf.io/p4thn ◽

2020 ◽

Author(s):

Gopi Krishna Erabati

Keyword(s):

Pose Estimation ◽

Autonomous Systems ◽

Microsoft Kinect ◽

Object Localization ◽

Initial Alignment ◽

Relative Localization ◽

3D Data ◽

Industry Automation ◽

Ofthe Object ◽

3D Descriptors

The technology in current research scenario is marching towards automation forhigher productivity with accurate and precise product development. Vision andRobotics are domains which work to create autonomous systems and are the keytechnology in quest for mass productivity. The automation in an industry canbe achieved by detecting interactive objects and estimating the pose to manipulatethem. Therefore the object localization ( i.e., pose) includes position andorientation of object, has profound ?significance. The application of object poseestimation varies from industry automation to entertainment industry and fromhealth care to surveillance. The objective of pose estimation of objects is verysigni?cant in many cases, like in order for the robots to manipulate the objects,for accurate rendering of Augmented Reality (AR) among others.This thesis tries to solve the issue of object pose estimation using 3D dataof scene acquired from 3D sensors (e.g. Kinect, Orbec Astra Pro among others).The 3D data has an advantage of independence from object texture and invarianceto illumination. The proposal is divided into two phases : An o?ine phasewhere the 3D model template of the object ( for estimation of pose) is built usingIterative Closest Point (ICP) algorithm. And an online phase where the pose ofthe object is estimated by aligning the scene to the model using ICP, providedwith an initial alignment using 3D descriptors (like Fast Point Feature Transform(FPFH)).The approach we develop is to be integrated on two di?erent platforms :1)Humanoid robot `Pyrene' which has Orbec Astra Pro 3D sensor for data acquisition,and 2)Unmanned Aerial Vehicle (UAV) which has Intel Realsense Euclidon it. The datasets of objects (like electric drill, brick, a small cylinder, cake box)are acquired using Microsoft Kinect, Orbec Astra Pro and Intel RealSense Euclidsensors to test the performance of this technique. The objects which are used totest this approach are the ones which are used by robot. This technique is testedin two scenarios, fi?rstly, when the object is on the table and secondly when theobject is held in hand by a person. The range of objects from the sensor is 0.6to 1.6m. This technique could handle occlusions of the object by hand (when wehold the object), as ICP can work even if partial object is visible in the scene.

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