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::Ptr cloud (new pcl::PointCloud); pcl::fromROSMsg (msg, *cloud); pcl::EuclideanClusterExtraction ece; std::vector 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 > _______________________________________________ > ros-users mailing list > ros-users@code.ros.org > https://code.ros.org/mailman/listinfo/ros-users