Description improved for Project#3 Computer Vision exercises, GSoC2025

Author: jmplaza

_pages/activities/gsoc/2025.md

@@ -74,17 +74,17 @@ Project #2 seeks to identify and address potential issues early on, fostering th
 - **Expected size**: 350h
 - **Mentors**: Pedro Arias (pedro.ariasp AT upm.es), Pawan Wadhwani (pawanw17 AT gmail.com) and Miguel Fernandez (miguel.fernandez.cortizas AT upm.es)
 
-## Project #3: Robotics-Academy: improve Deep Learning based exercises
+## Project #3: Robotics-Academy: improve Computer Vision exercises, including with real cameras
 
-**Brief explanation**: As of now, Robotics-Academy includes two exercises based on deep learning (DL): [digit classification](https://jderobot.github.io/RoboticsAcademy/exercises/ComputerVision/dl_digit_classifier) and [human detection](https://jderobot.github.io/RoboticsAcademy/exercises/ComputerVision/human_detection). These exercises allow users to submit a pre-trained DL model and benchmark its real-time performance in an easy and intuitive manner. Under the hood, we utilize [ONNX](https://onnx.ai/), which supports various formats for submitting trained models.
+**Brief explanation**: As of now, Robotics-Academy includes two deprecated Computer Vision exercises: [ColorFilter](https://jderobot.github.io/RoboticsAcademy/exercises/ComputerVision/color_filter) and [OpticalFlow Teleoperator](https://jderobot.github.io/RoboticsAcademy/exercises/ComputerVision/opticalflow_teleop). These exercises allow users to learn de foundations of image processing using OpenCV library. A Work-In-Progress from the JdeRobot Computer Vision Working Group is the multiplatform support of real cameras in RoboticsAcademy exercises (it works on Linux, Windows and MacOS machines), using WebRTC. 
 
-The main objective of this project is to enhance the robustness of these exercises and standardize their appearance and functionality. To achieve this, the exercises' frontend will be migrated to React, following the example of other exercises already functioning on our platform, such as Follow Line or Obstacle Avoidance. Additionally, we aim to briefly explore ONNX tools like model quantization or graph optimization to reduce the computational costs associated with running the exercises. Once we have addressed the issues related to robustness, appearance, and performance, we will update the documentation for all exercises, providing updated resources to guide students in their learning process.
+The main objective of this project is to prepare several exercises in RoboticsAcademy about Computer Vision (including the update of the previous two) which can be performed with real camera from the browser.
 
 {% include youtubePlayer.html id=page.youtubeId17 %}
 
-- **Skills required/preferred**: React, Python, Deep Learning, Git
+- **Skills required/preferred**: ComputerVision, OpenCV, React, Python
 - **Difficulty rating**: easy
-- **Expected results**: unified and robust deep learning exercises in Robotics-Academy
+- **Expected results**: new exercises on ComputerVision in Robotics-Academy, including with real cameras.
 - **Expected size**: 90h
 - **Mentors**: David Pascual (d.pascualhe AT gmail.com) and David Pérez (david.perez.saura AT upm.es)
 
@@ -147,7 +147,7 @@ You can read further about the tool on the [website](https://jderobot.github.io/
 - **Expected results**: A new robotics exercise in RoboticsAcademy using the Open3DEngine
 - **Expected size**: 175h
 - **Repository Link** - [Open 3D Engine](https://github.com/o3de/o3de), [RoboticsAcademy](https://github.com/JdeRobot/RoboticsAcademy), [RoboticsInfrastructure](https://github.com/JdeRobot/RoboticsInfrastructure)
-- **Mentors**: José M. Cañas (josemaria.plaza AT gmail.com) and Jan Hanca (jan AT hanca.pl)
+- **Mentors**: José M. Cañas (josemaria.plaza AT gmail.com) and Jan Hanca ( jan.hanca AT googlemail.com )
 
 
 ## Project #7: Robotics Academy: improvement of Gazebo scenarios and robot models