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<body>
<h1 id="benchmark-datasets-for-pedestrian-detection-action-recognition-and-fall-detection">Benchmark Datasets for Pedestrian Detection, Action Recognition, and Fall Detection</h1>
<h2 id="shu-miao%EF%BC%8Cguang-chen%EF%BC%8Cxiangyu-ning%EF%BC%8Cyang-zi">Shu Miao，Guang Chen，Xiangyu Ning，Yang Zi</h2>
<h3 id="institute-of-intelligent-network-vehicle-unversity-of-tongji-shanghai-china">Institute of Intelligent Network Vehicle, Unversity of Tongji, Shanghai, China</h3>
<img src="F:\MyDownloads/4.jpg" width="500" hegiht="313" align=center />
<ol>
<li>Recording Scene and Equipment</li>
</ol>
<img src="F:\MyDownloads/1.jpg" width="500" hegiht="313" align=center />
<p>The characteristics of the three datasets are summarized in Table 1, and they are described in detail below.</p>
<img src="F:\MyDownloads/5.jpg" width="500" hegiht="313" align=center />
<ol start="2">
<li>How to Get Datasets</li>
</ol>
<p>Because we upload all the data to the cloud server, if the user needs any dataset, you can click the corresponding download address.</p>
<ul>
<li>
<p>Pedestrian Detection Dataset</p>
<ul>
<li>Please download <a href="https://pan.baidu.com/s/1bwVDdRl7Hk2CwB6O3PRg4Q" title="With a Title">here</a></li>
</ul>
</li>
<li>
<p>Action Recognition Dataset</p>
<ul>
<li>Please download <a href="https://pan.baidu.com/s/1KcsMFO1tejfQTkfd-4A-og" title="With a Title">here</a></li>
</ul>
</li>
<li>
<p>Fall Detection Dataset</p>
<ul>
<li>Please download <a href="https://pan.baidu.com/s/1hYo6BPBd8m956ieXfVdCPQ" title="With a Title">here</a></li>
</ul>
</li>
</ul>
<ol start="3">
<li>How to Handle Datasets</li>
</ol>
<img src="F:\MyDownloads/2.jpg" width="500" hegiht="313" align=center />
<p>Conventional methods cannot process event data directly. Thus, we employ three encoding approaches59here as Frequency,SAE, (Surface of Active Events)and LIF, (Leaky60Integrate-and-Fire) to process continuous DVS event stream into a sequence of frame61images, in order to fit for conventional deep learning algorithms. We provide our codes (in Python) respect to three encoding approaches shown in folders.</p>
<ol start="4">
<li>Contacts</li>
</ol>
<p>Questions about these datasets should be directed to:
guang@in.tum.de</p>
<h2 id="for-further-details-please-related-to-our-paper">For further details please related to our paper.</h2>
</body>
</html>