TY - GEN
T1 - Using gamification to create and label photos that are challenging for computer vision and people
AU - Kotlinski, Piotr
AU - Chang, Xi Jing
AU - Chih-Yun, Yang
AU - Chiu, Wei-Chen
AU - Chang, Yung Ju
N1 - Publisher Copyright:
© 2020 Owner/Author.
PY - 2020/9/10
Y1 - 2020/9/10
N2 - It would be hard to overstate the importance of Computer Vision (CV), applications of which can be found from self-driving cars, through facial recognition to augmented reality and the healthcare industry. Recent years have witnessed dramatic progress in visual-object recognition, partially ascribable to the availability of labeled data. Unfortunately, recognition of obscure, unclear and ambiguous photos that are taken from unusual angles or distances remains a major challenge, as recently shown by the creation of the ObjectNet [1]. This paper complements that work via a game in which obscure, unclear and ambiguous photos are collaboratively created and labeled by the players, who adopt the role of detectives collecting evidence against in-game criminals. The game rules enforce the creation of images that are challenging to identify for CV and people alike, as a means of ensuring the high quality of players' input.
AB - It would be hard to overstate the importance of Computer Vision (CV), applications of which can be found from self-driving cars, through facial recognition to augmented reality and the healthcare industry. Recent years have witnessed dramatic progress in visual-object recognition, partially ascribable to the availability of labeled data. Unfortunately, recognition of obscure, unclear and ambiguous photos that are taken from unusual angles or distances remains a major challenge, as recently shown by the creation of the ObjectNet [1]. This paper complements that work via a game in which obscure, unclear and ambiguous photos are collaboratively created and labeled by the players, who adopt the role of detectives collecting evidence against in-game criminals. The game rules enforce the creation of images that are challenging to identify for CV and people alike, as a means of ensuring the high quality of players' input.
KW - computer vision
KW - gamification
KW - human-computer interactions
KW - mobile crowdsourcing
UR - http://www.scopus.com/inward/record.url?scp=85091854733&partnerID=8YFLogxK
U2 - 10.1145/3410530.3414420
DO - 10.1145/3410530.3414420
M3 - Conference contribution
AN - SCOPUS:85091854733
T3 - UbiComp/ISWC 2020 Adjunct - Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers
SP - 59
EP - 62
BT - UbiComp/ISWC 2020 Adjunct - Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers
PB - Association for Computing Machinery
T2 - 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and 2020 ACM International Symposium on Wearable Computers, UbiComp/ISWC 2020
Y2 - 12 September 2020 through 17 September 2020
ER -