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	<title>gophercg.log</title>
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	<description>code &#38; graphics, 3D CG, web</description>
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		<item>
		<title>Raytracing PCD as Implicit Surface</title>
		<link>http://gophercg.wordpress.com/2011/11/12/raytracing-pcd-as-implicit-surface-2/</link>
		<comments>http://gophercg.wordpress.com/2011/11/12/raytracing-pcd-as-implicit-surface-2/#comments</comments>
		<pubDate>Sat, 12 Nov 2011 16:33:01 +0000</pubDate>
		<dc:creator>gophercg</dc:creator>
				<category><![CDATA[GPGPU]]></category>
		<category><![CDATA[Point Cloud]]></category>
		<category><![CDATA[bunny]]></category>
		<category><![CDATA[CUDA]]></category>
		<category><![CDATA[filter]]></category>
		<category><![CDATA[Gaussian]]></category>
		<category><![CDATA[implicit surface]]></category>
		<category><![CDATA[normals]]></category>
		<category><![CDATA[octree]]></category>
		<category><![CDATA[PCD]]></category>
		<category><![CDATA[point cloud]]></category>
		<category><![CDATA[point sets]]></category>
		<category><![CDATA[raytracing]]></category>
		<category><![CDATA[realtime]]></category>
		<category><![CDATA[sampling]]></category>
		<category><![CDATA[statistical]]></category>
		<category><![CDATA[weighted]]></category>

		<guid isPermaLink="false">http://gophercg.wordpress.com/?p=895</guid>
		<description><![CDATA[Implicit surface: higher quality than disk render, more accurate surface silhouettes. Raytracing at interactive rates (video sped up) 3 clips: 1) No octree 2) In octree, radius 0.1: takes 60% time, very small speedup (compared to disk) since smooth surface requires more points. A denser model will benefit more from octree. 3) Radius 0.05: 36% [...]<img alt="" border="0" src="http://stats.wordpress.com/b.gif?host=gophercg.wordpress.com&amp;blog=3902671&amp;post=895&amp;subd=gophercg&amp;ref=&amp;feed=1" width="1" height="1" />]]></description>
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		<title>Hierarchical LOD by Clustering &amp; Frontface fix</title>
		<link>http://gophercg.wordpress.com/2011/11/06/hierarchical-lod-by-clustering-frontface-fix/</link>
		<comments>http://gophercg.wordpress.com/2011/11/06/hierarchical-lod-by-clustering-frontface-fix/#comments</comments>
		<pubDate>Sun, 06 Nov 2011 10:06:49 +0000</pubDate>
		<dc:creator>gophercg</dc:creator>
				<category><![CDATA[GPGPU]]></category>
		<category><![CDATA[Point Cloud]]></category>
		<category><![CDATA[clustering]]></category>
		<category><![CDATA[tree]]></category>
		<category><![CDATA[point cloud]]></category>
		<category><![CDATA[PCD]]></category>
		<category><![CDATA[octree]]></category>
		<category><![CDATA[hierarchical]]></category>
		<category><![CDATA[LOD]]></category>
		<category><![CDATA[algorithm]]></category>
		<category><![CDATA[frontface]]></category>

		<guid isPermaLink="false">http://gophercg.wordpress.com/?p=890</guid>
		<description><![CDATA[Clustering &#8211; Point Cloud Simplification Pointcloud simplify by iterative soft clustering algorithm Different from k-means, this currently is variable k-centroids not using global optimization. Local error weights. points: 704 clusters: 138 outliers: 11 Hole filling while simplifying is challenging. Many issues to solve including how to organize the new pointcloud in the existing octree. Hole [...]<img alt="" border="0" src="http://stats.wordpress.com/b.gif?host=gophercg.wordpress.com&amp;blog=3902671&amp;post=890&amp;subd=gophercg&amp;ref=&amp;feed=1" width="1" height="1" />]]></description>
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		<item>
		<title>Raytracing PCD as Implicit Surface</title>
		<link>http://gophercg.wordpress.com/2011/11/06/raytracing-pcd-as-implicit-surface/</link>
		<comments>http://gophercg.wordpress.com/2011/11/06/raytracing-pcd-as-implicit-surface/#comments</comments>
		<pubDate>Sun, 06 Nov 2011 07:18:12 +0000</pubDate>
		<dc:creator>gophercg</dc:creator>
				<category><![CDATA[GPGPU]]></category>
		<category><![CDATA[Point Cloud]]></category>
		<category><![CDATA[bunny]]></category>
		<category><![CDATA[CUDA]]></category>
		<category><![CDATA[filter]]></category>
		<category><![CDATA[Gaussian]]></category>
		<category><![CDATA[normals]]></category>
		<category><![CDATA[point cloud]]></category>
		<category><![CDATA[point sets]]></category>
		<category><![CDATA[sampling]]></category>
		<category><![CDATA[statistical]]></category>
		<category><![CDATA[weighted]]></category>

		<guid isPermaLink="false">http://gophercg.wordpress.com/?p=884</guid>
		<description><![CDATA[Iteratively project point x onto implicit surface, until x converges: a) Depth t MAX_T1_NEXT = OFF b) x1_fix threshold = 0.5 pixels MAX_T1_NEXT = 24 c) x1_fix threshold = 0.5 3D pixels x1_offray threshold = 0.5 pixels raysnap closer threshold = 0.5 3D pixels MAX_T1_NEXT = 24 d) x1_fix threshold = 0.5 3D pixels x1_offray [...]<img alt="" border="0" src="http://stats.wordpress.com/b.gif?host=gophercg.wordpress.com&amp;blog=3902671&amp;post=884&amp;subd=gophercg&amp;ref=&amp;feed=1" width="1" height="1" />]]></description>
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		<slash:comments>0</slash:comments>
	
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	</item>
		<item>
		<title>Diffuse 02 &#8211; Point Cloud Octree Raytracing</title>
		<link>http://gophercg.wordpress.com/2011/10/04/diffuse-02-point-cloud-octree-raytracing/</link>
		<comments>http://gophercg.wordpress.com/2011/10/04/diffuse-02-point-cloud-octree-raytracing/#comments</comments>
		<pubDate>Tue, 04 Oct 2011 03:21:09 +0000</pubDate>
		<dc:creator>gophercg</dc:creator>
				<category><![CDATA[GPGPU]]></category>
		<category><![CDATA[Point Cloud]]></category>
		<category><![CDATA[backface culling]]></category>
		<category><![CDATA[diffuse]]></category>
		<category><![CDATA[normals]]></category>
		<category><![CDATA[PCD]]></category>
		<category><![CDATA[point cloud]]></category>
		<category><![CDATA[point sets]]></category>
		<category><![CDATA[raytrace]]></category>

		<guid isPermaLink="false">http://gophercg.wordpress.com/?p=881</guid>
		<description><![CDATA[Video details: Diffuse pass, 1 directional light. 1) Octree partition artifact: overlap points duplicated across octree partitions to remove holes. 2) Redundant points from different leaves: fixed to avoid shading an overlap point twice. 3) Some backface and frontface fixes (a bit hacky), so the far frontface gets occluded by near frontface, regardless how large [...]<img alt="" border="0" src="http://stats.wordpress.com/b.gif?host=gophercg.wordpress.com&amp;blog=3902671&amp;post=881&amp;subd=gophercg&amp;ref=&amp;feed=1" width="1" height="1" />]]></description>
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		<slash:comments>0</slash:comments>
	
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	</item>
		<item>
		<title>CUDA: Raytracing PCD &amp; Octree</title>
		<link>http://gophercg.wordpress.com/2011/09/27/cuda-raytracing-pcd-octree/</link>
		<comments>http://gophercg.wordpress.com/2011/09/27/cuda-raytracing-pcd-octree/#comments</comments>
		<pubDate>Tue, 27 Sep 2011 03:36:41 +0000</pubDate>
		<dc:creator>gophercg</dc:creator>
				<category><![CDATA[GPGPU]]></category>
		<category><![CDATA[Point Cloud]]></category>
		<category><![CDATA[CUDA]]></category>
		<category><![CDATA[interactive]]></category>
		<category><![CDATA[octree]]></category>
		<category><![CDATA[PCD]]></category>
		<category><![CDATA[point cloud]]></category>
		<category><![CDATA[raytracer]]></category>
		<category><![CDATA[realtime]]></category>
		<category><![CDATA[tree]]></category>

		<guid isPermaLink="false">http://gophercg.wordpress.com/?p=869</guid>
		<description><![CDATA[video speed 4x. Screenshot explanations below. Interactive octree visualization of the bunny ears. Red shows leaf nodes, green internal nodes. Various pointers and memory issues finally fixed after a whole week merging the Nvidia traversal algorithm with the system. device time: 8.40~20.55ms host time: 39~156ms &#160; &#160; &#160; Raytracing oriented disks. Silhouette shows disk primitives, [...]<img alt="" border="0" src="http://stats.wordpress.com/b.gif?host=gophercg.wordpress.com&amp;blog=3902671&amp;post=869&amp;subd=gophercg&amp;ref=&amp;feed=1" width="1" height="1" />]]></description>
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			<media:title type="html">gophercg</media:title>
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	</item>
		<item>
		<title>GPU benchmark timing</title>
		<link>http://gophercg.wordpress.com/2011/09/14/gpu-benchmark-timing/</link>
		<comments>http://gophercg.wordpress.com/2011/09/14/gpu-benchmark-timing/#comments</comments>
		<pubDate>Wed, 14 Sep 2011 15:43:57 +0000</pubDate>
		<dc:creator>gophercg</dc:creator>
				<category><![CDATA[GPGPU]]></category>
		<category><![CDATA[benchmark]]></category>
		<category><![CDATA[CUDA]]></category>
		<category><![CDATA[event]]></category>

		<guid isPermaLink="false">http://gophercg.wordpress.com/?p=867</guid>
		<description><![CDATA[CPU timer: GLUT doesn&#8217;t work (only seconds resolution). Most suggest OS dependent code. I used some public code that works on Linux &#38; Windows. GPU timer works. Resolution about 0.5 millisecond. I packaged up some code from the programming guide: cudaEvent_t start, stop; float time; void cudaTimeStart(){ cudaEventCreate(&#38;start); cudaEventCreate(&#38;stop); cudaEventRecord( start, 0 ); } void [...]<img alt="" border="0" src="http://stats.wordpress.com/b.gif?host=gophercg.wordpress.com&amp;blog=3902671&amp;post=867&amp;subd=gophercg&amp;ref=&amp;feed=1" width="1" height="1" />]]></description>
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		<slash:comments>0</slash:comments>
	
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			<media:title type="html">gophercg</media:title>
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	</item>
		<item>
		<title>CUDA notes: kernel memory &amp; variables</title>
		<link>http://gophercg.wordpress.com/2011/09/11/cuda-kernel-notes/</link>
		<comments>http://gophercg.wordpress.com/2011/09/11/cuda-kernel-notes/#comments</comments>
		<pubDate>Sun, 11 Sep 2011 07:33:12 +0000</pubDate>
		<dc:creator>gophercg</dc:creator>
				<category><![CDATA[code]]></category>
		<category><![CDATA[GPGPU]]></category>
		<category><![CDATA[CUDA]]></category>
		<category><![CDATA[local memory]]></category>
		<category><![CDATA[kernel]]></category>

		<guid isPermaLink="false">http://gophercg.wordpress.com/?p=851</guid>
		<description><![CDATA[Some following errors may be due to other compounded reasons, treat them as suggestions and confirm in your own code. All kernel local variables allocated in sequence. Each variable must suit alignment req. Variables that violate alignment will affect variables allocated afterwards. Don&#8217;t initialize variables anywhere in loops (eg int i iterator in for(;;)). Caused [...]<img alt="" border="0" src="http://stats.wordpress.com/b.gif?host=gophercg.wordpress.com&amp;blog=3902671&amp;post=851&amp;subd=gophercg&amp;ref=&amp;feed=1" width="1" height="1" />]]></description>
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		<slash:comments>0</slash:comments>
	
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		<item>
		<title>CUDA raytrace first images</title>
		<link>http://gophercg.wordpress.com/2011/09/11/cuda-raytrace-first-images/</link>
		<comments>http://gophercg.wordpress.com/2011/09/11/cuda-raytrace-first-images/#comments</comments>
		<pubDate>Sun, 11 Sep 2011 04:33:16 +0000</pubDate>
		<dc:creator>gophercg</dc:creator>
				<category><![CDATA[GPGPU]]></category>
		<category><![CDATA[Point Cloud]]></category>
		<category><![CDATA[backface culling]]></category>
		<category><![CDATA[CUDA]]></category>
		<category><![CDATA[normals]]></category>
		<category><![CDATA[point cloud]]></category>
		<category><![CDATA[point sets]]></category>
		<category><![CDATA[raytrace]]></category>

		<guid isPermaLink="false">http://gophercg.wordpress.com/?p=852</guid>
		<description><![CDATA[9/10/2011 First CUDA images. It&#8217;s been a long way setting up the dev env, and learning basics of CUDA. Especially memory and some syntax have high learning curve. Finding and cooperating with helper libraries is also a challenge, and spend days fixing compiler/linker parameters. Currently only x64 bit release configuration works, and debug config is [...]<img alt="" border="0" src="http://stats.wordpress.com/b.gif?host=gophercg.wordpress.com&amp;blog=3902671&amp;post=852&amp;subd=gophercg&amp;ref=&amp;feed=1" width="1" height="1" />]]></description>
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		<slash:comments>0</slash:comments>
	
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			<media:title type="html">gophercg</media:title>
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		<media:content url="http://www.gophercg.com/thesis/render_CUDA/render_CUDA1_files/image001.gif" medium="image" />

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		<item>
		<title>Backface culling &amp; Octree</title>
		<link>http://gophercg.wordpress.com/2011/09/11/backface-culling-octree/</link>
		<comments>http://gophercg.wordpress.com/2011/09/11/backface-culling-octree/#comments</comments>
		<pubDate>Sun, 11 Sep 2011 03:37:25 +0000</pubDate>
		<dc:creator>gophercg</dc:creator>
				<category><![CDATA[Point Cloud]]></category>
		<category><![CDATA[backface culling]]></category>
		<category><![CDATA[normals]]></category>
		<category><![CDATA[octree construction]]></category>
		<category><![CDATA[point cloud]]></category>
		<category><![CDATA[point sets]]></category>
		<category><![CDATA[raytrace]]></category>
		<category><![CDATA[recursive traversal]]></category>

		<guid isPermaLink="false">http://gophercg.wordpress.com/?p=846</guid>
		<description><![CDATA[Backface cull Only slight speed up, because more set checking overhead, but may help more on high point count. backface may mess up contour because backfacing points at contours contribute to normals blending. BENCHMARK setup general 0.0053 r_max setup 0.0017 r_max prune 1.1013 raytrace loop 9.2197 rescale normal-&#62;color 0.0513 profiler (CPU time): 16 seconds Shrink [...]<img alt="" border="0" src="http://stats.wordpress.com/b.gif?host=gophercg.wordpress.com&amp;blog=3902671&amp;post=846&amp;subd=gophercg&amp;ref=&amp;feed=1" width="1" height="1" />]]></description>
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		<title>Update 05/07/2011: Normals Fix &amp; Radius Learning</title>
		<link>http://gophercg.wordpress.com/2011/07/29/update-05072011-normals-fix-radius-learning/</link>
		<comments>http://gophercg.wordpress.com/2011/07/29/update-05072011-normals-fix-radius-learning/#comments</comments>
		<pubDate>Fri, 29 Jul 2011 10:04:23 +0000</pubDate>
		<dc:creator>gophercg</dc:creator>
				<category><![CDATA[Point Cloud]]></category>
		<category><![CDATA[bilateral]]></category>
		<category><![CDATA[bunny]]></category>
		<category><![CDATA[estimation]]></category>
		<category><![CDATA[feature aware]]></category>
		<category><![CDATA[filter]]></category>
		<category><![CDATA[Gaussian]]></category>
		<category><![CDATA[normals]]></category>
		<category><![CDATA[point cloud]]></category>
		<category><![CDATA[point sets]]></category>
		<category><![CDATA[sampling]]></category>
		<category><![CDATA[sharpen]]></category>
		<category><![CDATA[statistical]]></category>
		<category><![CDATA[trilateral]]></category>
		<category><![CDATA[unification]]></category>
		<category><![CDATA[weighted]]></category>

		<guid isPermaLink="false">http://gophercg.wordpress.com/?p=840</guid>
		<description><![CDATA[Introduction Normals fixes page 1. r radius estimation page 6. Unify Normals BSP is very fast but has a percentage of failed unifications at sharper regions, and required tuning the r radii by remapping the per point r. MST ran for 2 hours but could not finish. The following explain each improvement to minimize failed [...]<img alt="" border="0" src="http://stats.wordpress.com/b.gif?host=gophercg.wordpress.com&amp;blog=3902671&amp;post=840&amp;subd=gophercg&amp;ref=&amp;feed=1" width="1" height="1" />]]></description>
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