Week12: Demo, User Study, Feedback, and Acknowledgement
1. Demo
We upload the video demonstrating our system at the youtube and below URL will direct you to the demo video.
https://www.youtube.com/watch?v=49FvM7HNh3E
2.User study
We conducted user study because we found the importance on investigating how the potential user find this system useful for decreasing the physical burden and how system itself is not burdening. For designing the user study, we put improtance on physical burden because that is our main things that should be addressed to solve the problem the people with physical impairment have. With the participants engagement in the user study, we could assess the needs in system from different perspective and validate the system. We also filmed and edited the process of user study, but we are going to keep it as private video to keep the privacy of participants.
3. Feedback
We got the feedback after presentation. We tried to address the question expressed in some of the comments here.
Q. Is the system can recognize all the size of the objects?
It is depends on the kernel size our model using. If the size of the object is not that small with low detection score, we can decrease a threshold value, or increase object part of image and rerun the model.
Q. Consider multi-quantity itme. eq. what if there are 2 laptops. How to distinguish?
Our system return all laptops. So users can pick one of laptops.
Q. Taking some time to find an object takes so much time
We don't think that 10 seconds is "so much time" for comparing the delay for searching all area in the building. From the user study, we could see that the users who experienced the task of finding items in indoor environment rather find our system useful for decreasing the time taken for finding the an object.
Q. Security/privacy issues
We also think we need to consider those part. With our background and limitation of time, we decided to decrease the time of recording. In the future work, we agree with focusing on security and privacy issues.
Q. Works only in familiar environment
Our system can be implemented in all environment. Therefore, It could be expanded to other indoor environment where the users are not familiar with.
4.Acknowledgement
This is the last blog for this course project. We first want to deliver our sincere gratitude for Dr, Min and our classmates' supports and advising throughout this semester. Life is short to meet all the 6 billion people, but we are thankful to meet you and know you in class and life. So, THANK YOU ALL AGAIN.
We upload the video demonstrating our system at the youtube and below URL will direct you to the demo video.
https://www.youtube.com/watch?v=49FvM7HNh3E
2.User study
We conducted user study because we found the importance on investigating how the potential user find this system useful for decreasing the physical burden and how system itself is not burdening. For designing the user study, we put improtance on physical burden because that is our main things that should be addressed to solve the problem the people with physical impairment have. With the participants engagement in the user study, we could assess the needs in system from different perspective and validate the system. We also filmed and edited the process of user study, but we are going to keep it as private video to keep the privacy of participants.
3. Feedback
We got the feedback after presentation. We tried to address the question expressed in some of the comments here.
Q. Is the system can recognize all the size of the objects?
It is depends on the kernel size our model using. If the size of the object is not that small with low detection score, we can decrease a threshold value, or increase object part of image and rerun the model.
Q. Consider multi-quantity itme. eq. what if there are 2 laptops. How to distinguish?
Our system return all laptops. So users can pick one of laptops.
Q. Taking some time to find an object takes so much time
We don't think that 10 seconds is "so much time" for comparing the delay for searching all area in the building. From the user study, we could see that the users who experienced the task of finding items in indoor environment rather find our system useful for decreasing the time taken for finding the an object.
Q. Security/privacy issues
We also think we need to consider those part. With our background and limitation of time, we decided to decrease the time of recording. In the future work, we agree with focusing on security and privacy issues.
Q. Works only in familiar environment
Our system can be implemented in all environment. Therefore, It could be expanded to other indoor environment where the users are not familiar with.
4.Acknowledgement
This is the last blog for this course project. We first want to deliver our sincere gratitude for Dr, Min and our classmates' supports and advising throughout this semester. Life is short to meet all the 6 billion people, but we are thankful to meet you and know you in class and life. So, THANK YOU ALL AGAIN.
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