https://mw.hh.se/caisr/index.php?action=history&feed=atom&title=Object_Tracking_and_Anticipation 2026-04-04T17:53:15Z Revision history for this page on the wiki MediaWiki 1.35.13 https://mw.hh.se/caisr/index.php?title=Object_Tracking_and_Anticipation&diff=5435&oldid=prev 2024-09-23T10:06:16Z

<p></p> <table class="diff diff-contentalign-left diff-editfont-monospace" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en"> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Older revision</td> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 10:06, 23 September 2024</td> </tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l1" >Line 1:</td> <td colspan="2" class="diff-lineno">Line 1:</td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>{{StudentProjectTemplate</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>{{StudentProjectTemplate</div></td></tr> <tr><td class='diff-marker'>−</td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>|Summary=The thesis presents an experimental study of different object-tracking and trajectory anticipation algorithms in the context of autonomous driving. <del class="diffchange diffchange-inline">The student will analyze how different deep learning-based tracking and anticipation algorithms work in scenes with falling snowflakes.  </del></div></td><td class='diff-marker'>+</td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>|Summary=The thesis presents an experimental study of different object-tracking and trajectory anticipation algorithms in the context of autonomous driving. <ins class="diffchange diffchange-inline">  </ins></div></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|Prerequisites=A solid background in Python</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|Prerequisites=A solid background in Python</div></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>and Machine Learning.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>and Machine Learning.</div></td></tr> </table>

Islab https://mw.hh.se/caisr/index.php?title=Object_Tracking_and_Anticipation&diff=5434&oldid=prev 2024-09-23T10:05:06Z

<p></p> <table class="diff diff-contentalign-left diff-editfont-monospace" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en"> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Older revision</td> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 10:05, 23 September 2024</td> </tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l1" >Line 1:</td> <td colspan="2" class="diff-lineno">Line 1:</td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>{{StudentProjectTemplate</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>{{StudentProjectTemplate</div></td></tr> <tr><td class='diff-marker'>−</td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>|Summary=The thesis presents an experimental study of different object-tracking and trajectory anticipation algorithms in the context of autonomous driving. The student will analyze how different tracking and anticipation algorithms in scenes with falling snowflakes. <del class="diffchange diffchange-inline">Given the detected object bounding boxes, the student will experiment with Kalman Filtering, Extended Kalman Filtering, Particle Filtering, and Deep Learning-based tracking methods.  </del></div></td><td class='diff-marker'>+</td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>|Summary=The thesis presents an experimental study of different object-tracking and trajectory anticipation algorithms in the context of autonomous driving. The student will analyze how different <ins class="diffchange diffchange-inline">deep learning-based </ins>tracking and anticipation algorithms <ins class="diffchange diffchange-inline">work </ins>in scenes with falling snowflakes. <ins class="diffchange diffchange-inline">  </ins></div></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|Prerequisites=A solid background in Python</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|Prerequisites=A solid background in Python</div></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>and Machine Learning.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>and Machine Learning.</div></td></tr> </table>

Islab https://mw.hh.se/caisr/index.php?title=Object_Tracking_and_Anticipation&diff=5433&oldid=prev 2024-09-23T10:04:00Z

<p></p> <table class="diff diff-contentalign-left diff-editfont-monospace" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en"> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Older revision</td> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 10:04, 23 September 2024</td> </tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l1" >Line 1:</td> <td colspan="2" class="diff-lineno">Line 1:</td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>{{StudentProjectTemplate</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>{{StudentProjectTemplate</div></td></tr> <tr><td class='diff-marker'>−</td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>|Summary=The thesis presents an experimental study of different object-tracking and trajectory anticipation algorithms in the context of autonomous driving. The student will analyze how different tracking and anticipation algorithms in scenes with falling snowflakes. Given the detected object bounding boxes, the student will experiment with Kalman Filtering, Extended Kalman Filtering, Particle Filtering, and Deep Learning-based tracking methods. <del class="diffchange diffchange-inline">As a dataset, the student will use CADC together with a custom object detection method. The thesis will be carried out as part of an EU project ROADVIEW.</del></div></td><td class='diff-marker'>+</td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>|Summary=The thesis presents an experimental study of different object-tracking and trajectory anticipation algorithms in the context of autonomous driving. The student will analyze how different tracking and anticipation algorithms in scenes with falling snowflakes. Given the detected object bounding boxes, the student will experiment with Kalman Filtering, Extended Kalman Filtering, Particle Filtering, and Deep Learning-based tracking methods. <ins class="diffchange diffchange-inline"> </ins></div></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|Prerequisites=A solid background in Python</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|Prerequisites=A solid background in Python</div></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>and Machine Learning.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>and Machine Learning.</div></td></tr> </table>

Islab https://mw.hh.se/caisr/index.php?title=Object_Tracking_and_Anticipation&diff=5432&oldid=prev 2024-09-23T08:58:02Z

<p>Created page with &quot;{{StudentProjectTemplate |Summary=The thesis presents an experimental study of different object-tracking and trajectory anticipation algorithms in the context of autonomous dr...&quot;</p> <p><b>New page</b></p><div>{{StudentProjectTemplate<br /> |Summary=The thesis presents an experimental study of different object-tracking and trajectory anticipation algorithms in the context of autonomous driving. The student will analyze how different tracking and anticipation algorithms in scenes with falling snowflakes. Given the detected object bounding boxes, the student will experiment with Kalman Filtering, Extended Kalman Filtering, Particle Filtering, and Deep Learning-based tracking methods. As a dataset, the student will use CADC together with a custom object detection method. The thesis will be carried out as part of an EU project ROADVIEW.<br /> |Prerequisites=A solid background in Python<br /> and Machine Learning.<br /> |Supervisor=Eren Aksoy<br /> |Level=Master<br /> |Status=Open<br /> }}</div>

Islab