From bca011051c5aaf3c1a1f8f470caced8f0d9da1ab Mon Sep 17 00:00:00 2001
From: Chiara Santoro <cs.chiarasantoro@gmail.com>
Date: Sat, 25 Apr 2026 23:01:49 +0200
Subject: [PATCH] group_o index.html

---
 index.html | 27 +++++++++++++++++++++++++++
 1 file changed, 27 insertions(+)

diff --git a/index.html b/index.html
index cd75335..2c93a9d 100644
--- a/index.html
+++ b/index.html
@@ -248,6 +248,30 @@ <h3>Facial Expression Recognition with Hybrid Models</h3>
               </label>
             </div>
           </article>
+
+         <article class="project-card">
+            <div class="teaser" role="img" aria-label="Promptable Video Event Finder with Segmentation-Guided Motion Analysis.">
+              <!--<img src="assets/group M.png" alt="Highlights Preview" style="position:absolute; inset:0; width:100%; height:100%; object-fit:cover; z-index:2;">-->
+              <span class="teaser-label" style="z-index:3;">Group O</span>
+            </div>
+            <div class="project-content">
+              <p class="project-meta">Segmentation, Object detection, tracking, foundation models</p>
+              <h3>Smart Event Detection for Highlight Clips</h3>
+              <p class="project-abstract">
+                Have you ever missed a highlight during a match? This system can capture highlights based on a user prompt or directly from a video.
+                It uses advanced, state-of-the-art approaches—such as Meta’s SAM3—to track objects, detect events, and generate short highlight clips.
+                <br><br>
+                The goal is to combine modern segmentation models (such as SAM) with classical computer vision techniques. Segmentation serves as a strong perception layer, while event detection is driven by motion-based features such as trajectories, velocity, and frequency analysis, along with lightweight reasoning.
+                The system follows a modular design, consisting of a general perception and feature extraction pipeline combined with task-specific event detection modules.
+                 <br><br>
+                The system is primarily designed for human action detection (e.g., waving, raising a hand, standing up). As an extension, it can also handle simple sports scenarios, such as tracking a ball moving toward or crossing a goal, demonstrating its ability to generalize to multi-object interactions.
+              <label class="project-toggle-label">
+                <input class="project-toggle" type="checkbox" aria-label="Toggle full project pitch">
+                <span class="project-toggle-more">Read more</span>
+                <span class="project-toggle-less">Show less</span>
+              </label>
+            </div>
+          </article>
         
 
           <article class="project-card add-project-card">
@@ -258,6 +282,9 @@ <h3>Facial Expression Recognition with Hybrid Models</h3>
             </a>
           </article>
 
+          
+
+
         </div>
 
       </div>