[ros-users] Simplest way to segment spatially separated objects in point clouds?

Björn Giesler bjoern at giesler.de
Mon Apr 18 16:53:46 UTC 2011


thanks for the code! I've tried it, and it runs... but either it gets stuck in an infinite loop or it takes a very long time (>10min.) for one image. Can that be right? I've tried debugging into it, but this is over my head...


Am 18.04.2011 um 17:59 schrieb Zoltan-Csaba Marton:

> Hi Björn,
> PCL has euclidean cluster extraction function and class and also convex
> hull.. but there is no tutorial for it yet. Nonetheless, it is very
> simple to use. Here is a hacked together sample code (suppose msg is
> your sensor_msgs::PointCloud2 input):
> pcl::PointCloud<PointT>::Ptr cloud
>  (new pcl::PointCloud<pcl::PointXYZRGB>);
> pcl::fromROSMsg (msg, *cloud);
> pcl::EuclideanClusterExtraction<pcl::PointXYZRGB> ece;
> std::vector<pcl::PointIndices> clusters;
> ece.setInputCloud (cloud);
> ece.setMinClusterSize (10);
> ece.setClusterTolerance (0.05);
> ece.extract (clusters);
> ROS_INFO_STREAM ("No of clusters: " << clusters.size () << std::endl);
> Hope this helps.
> Cheers,
> Zoltan
> On Mon, 2011-04-18 at 17:35 +0200, Björn Giesler wrote:
>> Hi all,
>> I'd like to use my robot's Kinect to find objects (obstacles / humans) in 3D. The way the sensor is integrated, it cannot see the ground plane, so segmentation should be very easy because no objects are connected by any structure. What I'm looking for is the simplest way to segment the point cloud into non-connected sub clouds or convex hulls thereof. I've found the border extraction tutorial, which kind of seems to do what I want... Is that it or is there an even simpler way?
>> Thanks a lot & regards,
>> Björn
>> Von meinem iPad gesendet
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Björn Giesler
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