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@@ -259,12 +259,13 @@ <h3>Facial Expression Recognition with Hybrid Models</h3>
               <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.
+                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.
+                </p>
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