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#OpticalFlow

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Karsten Schmidt<p>There's a whole bunch of recent <a href="https://mastodon.thi.ng/tags/ThingUmbrella" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ThingUmbrella</span></a> updates which I still have to write about, but one of the things is the reworked, improved and more customizable optical flow (aka <a href="https://thi.ng/pixel-flow" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">thi.ng/pixel-flow</span><span class="invisible"></span></a> package). The visualization in this test video is showing it in action via color-coded overlaid flow field vectors (once again worst-case scenario for video compression, let's see how it comes out [or not...])</p><p><a href="https://mastodon.thi.ng/tags/OpticalFlow" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpticalFlow</span></a> <a href="https://mastodon.thi.ng/tags/DataViz" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataViz</span></a> <a href="https://mastodon.thi.ng/tags/Visualization" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Visualization</span></a> <a href="https://mastodon.thi.ng/tags/TypeScript" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TypeScript</span></a> <a href="https://mastodon.thi.ng/tags/Video" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Video</span></a></p>
Karsten Schmidt<p>To avoid a massive OpenCV dependency for a current project I'm involved in, I ended up porting my own homemade, naive optical flow code from 2008 and just released it as a new package. Originally this was written for a gestural UI system for Nokia retail stores (prior to the Microsoft takeover), the package readme contains another short video showing the flow field being utilized to rotate a 3D cube:</p><p><a href="https://thi.ng/pixel-flow" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">thi.ng/pixel-flow</span><span class="invisible"></span></a></p><p>I've also created a small new example project for testing with either webcam or videos:</p><p><a href="https://demo.thi.ng/umbrella/optical-flow/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">demo.thi.ng/umbrella/optical-f</span><span class="invisible">low/</span></a></p><p><a href="https://mastodon.thi.ng/tags/ThingUmbrella" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ThingUmbrella</span></a> <a href="https://mastodon.thi.ng/tags/OpticalFlow" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpticalFlow</span></a> <a href="https://mastodon.thi.ng/tags/ImageAnalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ImageAnalysis</span></a> <a href="https://mastodon.thi.ng/tags/ComputerVision" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ComputerVision</span></a> <a href="https://mastodon.thi.ng/tags/TypeScript" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TypeScript</span></a> <a href="https://mastodon.thi.ng/tags/JavaScript" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>JavaScript</span></a></p>
Karsten Schmidt<p>From my old Vimeo archive (2008): <a href="https://mastodon.thi.ng/tags/OpticalFlow" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpticalFlow</span></a> <a href="https://mastodon.thi.ng/tags/3D" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>3D</span></a> <a href="https://mastodon.thi.ng/tags/InteractionDesign" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>InteractionDesign</span></a> prototype for Nokia retail stores. No OpenCV, just vanilla pixel buffer analysis (in Java):</p><p>"Documenting progress for a current project, using optical flow analysis to enable a gestural interface &amp; navigate on-screen content both 2D and 3D.</p><p>The video analysis requires only a very small (here 160 x 120) capture size and is fairly tolerant to noise. Each frame is recursively analysed in blocks of 30x30 pixels (variable) which are displaced by a certain amount (also adaptable) and then checked for matches in the previous frame. The resulting flow field is displayed and summed to compute the average direction and amount of movement. All calculations and updates to the flow field use threshold &amp; low pass filters to reduce jitter."</p>
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