Collaborative: Gesture Recognition Challenge

这项研究的目的是促进视频数据处理(尤其是手势识别)领域的发展，并说明深度学习体系和迁移学习的力量。方法是组织一次挑战，最终在会议现场进行一次生活评估。智力价值：最近在自适应和智能系统(AIS)中的许多研究牺牲了设计接近人类智能的系统的宏伟目标，以解决具有实际意义的数据挖掘任务，并获得更直接的回报。该项目为受神经网络启发的深度学习体系结构提供了一个机会，以展示它们解决更复杂问题的能力，这些问题需要将知识从一个任务转移到另一个任务(转移学习)，利用与手势识别目标任务不直接相关的视频数据的可用性。参与者还将参与数据交换，以扩大前所未有的大型和多样化的手势数据库。更广泛的影响：事实证明，挑战是研究的巨大刺激。为了产生长期的影响，挑战平台以及数据和软件储存库将在国家科学基金会资助的项目期限结束后继续开放。该项目的教育部分包括让学生参与比赛，提供直接用于教学课程的材料，以及向高中生演示手势识别，让他们接触到计算机视觉研究和手语交流。我们与聋人社区的联系将使我们能够利用这项研究的产品来推动辅助技术的发展。

The objective of this research is both to advance the field of video data processing (more particularly gesture recognition) and to illustrate the power of deep learning architectures and transfer learning. The approach is to organize a challenge culminating in a life evaluation at the site of a conference.Intellectual merit: Much of the recent research in Adaptive and Intelligent Systems (AIS) has sacrificed the grand goal of designing systems ever approaching human intelligence for solving data mining tasks of practical interest with more immediate reward. This project gives an opportunity to deep learning architectures inspired by neural networks to demonstrate their ability to address more complex problems requiring to transfer knowledge from task to task (transfer learning), leveraging the availability of video data not directly related to the target task of gesture recognition. The participants will also be involved in a data exchange to grow an unprecedented large and diverse database of gestures. Broader Impact: Challenges have proved to be a great stimulus of research. For a long lasting impact, the challenge platform and the data and software repositories will remain open beyond the term of the NSF funded project. The educational components of the project include engaging students in the contest, providing material directly usable in teaching curricula, and demonstrating gesture recognition to high school students to expose them to computer vision research and sign language communication. Our connections with the deaf community will allow us to gear the product of this research to advance assistive technology.