All Outputs (3)

I2R VC @ ImageClef2017: Ensemble of Deep Learnt Features for Lifelog Video Summarization (2017)
Conference Proceeding
Molino, A., Mandal, B., Jie, L., Lim, J., Subbaraju, V., & Chandrasekhar, V. (2017). I2R VC @ ImageClef2017: Ensemble of Deep Learnt Features for Lifelog Video Summarization.

In this paper we describe our approach for the ImageCLEF-lifelog summarization task. A total of ten runs were submitted, which used only visual features, only metadata information, or both. In the first step, a set of relevant frames are drawn from t... Read More about I2R VC @ ImageClef2017: Ensemble of Deep Learnt Features for Lifelog Video Summarization.

An empirical approach for automatic face clustering on personal lifelogging images (2017)
Conference Proceeding
Subbaraju, V., Xu, Q., Mandal, B., Li, L., & Lim, J. (2017). An empirical approach for automatic face clustering on personal lifelogging images. . https://doi.org/10.1109/siprocess.2017.8124519

Life-logging applications generate a vast amount of personalized data that provides vital insights into the user's daily life. One such key insight is the people whom the user has come across/interacted with during regular life. This can be obtained... Read More about An empirical approach for automatic face clustering on personal lifelogging images.

Analysis of Human Attentions for Face Recognition on Natural Videos and Comparison with CV Algorithm on Performance (2017)
Conference Proceeding
Ragab Sayed, M., Yuting Lim, R., Mandal, B., Li, L., Hwee Lim, J., & Sim, T. (2017). Analysis of Human Attentions for Face Recognition on Natural Videos and Comparison with CV Algorithm on Performance. In No. 7: Science of Intelligence: Computational Principles of Natural and Artificial Intelligence

Researchers have conducted many studies on human attentions and their eye gaze patterns for face recognition (FR), hoping to inspire new ideas to develop computer vision (CV) algorithms which perform like or even better than human. Yet, while these s... Read More about Analysis of Human Attentions for Face Recognition on Natural Videos and Comparison with CV Algorithm on Performance.