<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:wfw="http://wellformedweb.org/CommentAPI/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
	xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
	>

<channel>
	<title>Visual tracking Archives &#8212; MATLAB Number ONE</title>
	<atom:link href="https://matlab1.com/product-tag/visual-tracking/feed/" rel="self" type="application/rss+xml" />
	<link>https://matlab1.com/product-tag/visual-tracking/</link>
	<description>MATLAB Simulink &#124; Tutorial &#124; Code &#124; Project</description>
	<lastBuildDate>Sun, 22 Jan 2023 04:15:04 +0000</lastBuildDate>
	<language>en-GB</language>
	<sy:updatePeriod>
	hourly	</sy:updatePeriod>
	<sy:updateFrequency>
	1	</sy:updateFrequency>
	

<image>
	<url>https://matlab1.com/wp-content/uploads/2018/08/icon1-100x100.png</url>
	<title>Visual tracking Archives &#8212; MATLAB Number ONE</title>
	<link>https://matlab1.com/product-tag/visual-tracking/</link>
	<width>32</width>
	<height>32</height>
</image> 
	<item>
		<title>Robust object tracking via active feature selection</title>
		<link>https://matlab1.com/shop/matlab-code/robust-object-tracking-via-active-feature-selection/</link>
					<comments>https://matlab1.com/shop/matlab-code/robust-object-tracking-via-active-feature-selection/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Sun, 15 Apr 2018 13:43:50 +0000</pubDate>
				<guid isPermaLink="false">https://matlab1.com/?post_type=product&#038;p=4960</guid>

					<description><![CDATA[<p>In this project, we proposed a robust tracker based on an online discriminative appearance model. In order to design a robust appearance model, we developed an online active feature selection (AFS) approach via minimizing a Fishier information criterion. We showed that the features selected by our proposed online AFS boosting algorithm are much more informative and discriminative than those selected by [&#8230;]</p>
<p>The post <a href="https://matlab1.com/shop/matlab-code/robust-object-tracking-via-active-feature-selection/">Robust object tracking via active feature selection</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
]]></description>
		
					<wfw:commentRss>https://matlab1.com/shop/matlab-code/robust-object-tracking-via-active-feature-selection/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>Optical Flow for person tracking in infrared video</title>
		<link>https://matlab1.com/shop/matlab-code/optical-flow-person-tracking-infrared-video/</link>
					<comments>https://matlab1.com/shop/matlab-code/optical-flow-person-tracking-infrared-video/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Mon, 29 Aug 2016 12:08:09 +0000</pubDate>
				<guid isPermaLink="false">https://matlab1.com/?post_type=product&#038;p=685</guid>

					<description><![CDATA[<p>Optical Flow is one the method for object tracking in video. In this MATLAB Code, We use OTCBVS dataset for evaluation of our algorithm. Our code can detect collisions between two people, but the number considered to a person after the collision, does not change.</p>
<p>The post <a href="https://matlab1.com/shop/matlab-code/optical-flow-person-tracking-infrared-video/">Optical Flow for person tracking in infrared video</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
]]></description>
		
					<wfw:commentRss>https://matlab1.com/shop/matlab-code/optical-flow-person-tracking-infrared-video/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>Particle filter based on Particle Swarm Optimization resampling for vision tracking</title>
		<link>https://matlab1.com/shop/matlab-code/particle-filter-based-particle-swarm-optimization-resampling-vision-tracking/</link>
					<comments>https://matlab1.com/shop/matlab-code/particle-filter-based-particle-swarm-optimization-resampling-vision-tracking/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Mon, 29 Aug 2016 08:45:11 +0000</pubDate>
				<guid isPermaLink="false">https://matlab1.com/?post_type=product&#038;p=681</guid>

					<description><![CDATA[<p>Particle filter based on Particle Swarm Optimization resampling for vision tracking reference paper : Zhang, Miaohui, Ming Xin, and Jie Yang. &#8220;Adaptive multi-cue based particle swarm optimization guided particle filter tracking in infrared videos.&#8221; Neurocomputing 122 (2013): 163-171.</p>
<p>The post <a href="https://matlab1.com/shop/matlab-code/particle-filter-based-particle-swarm-optimization-resampling-vision-tracking/">Particle filter based on Particle Swarm Optimization resampling for vision tracking</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
]]></description>
		
					<wfw:commentRss>https://matlab1.com/shop/matlab-code/particle-filter-based-particle-swarm-optimization-resampling-vision-tracking/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
	</channel>
</rss>
