48 research outputs found
CLERA: A Unified Model for Joint Cognitive Load and Eye Region Analysis in the Wild
Non-intrusive, real-time analysis of the dynamics of the eye region allows us
to monitor humans' visual attention allocation and estimate their mental state
during the performance of real-world tasks, which can potentially benefit a
wide range of human-computer interaction (HCI) applications. While commercial
eye-tracking devices have been frequently employed, the difficulty of
customizing these devices places unnecessary constraints on the exploration of
more efficient, end-to-end models of eye dynamics. In this work, we propose
CLERA, a unified model for Cognitive Load and Eye Region Analysis, which
achieves precise keypoint detection and spatiotemporal tracking in a
joint-learning framework. Our method demonstrates significant efficiency and
outperforms prior work on tasks including cognitive load estimation, eye
landmark detection, and blink estimation. We also introduce a large-scale
dataset of 30k human faces with joint pupil, eye-openness, and landmark
annotation, which aims to support future HCI research on human factors and
eye-related analysis.Comment: ACM Transactions on Computer-Human Interactio
ChimpACT: A Longitudinal Dataset for Understanding Chimpanzee Behaviors
Understanding the behavior of non-human primates is crucial for improving
animal welfare, modeling social behavior, and gaining insights into
distinctively human and phylogenetically shared behaviors. However, the lack of
datasets on non-human primate behavior hinders in-depth exploration of primate
social interactions, posing challenges to research on our closest living
relatives. To address these limitations, we present ChimpACT, a comprehensive
dataset for quantifying the longitudinal behavior and social relations of
chimpanzees within a social group. Spanning from 2015 to 2018, ChimpACT
features videos of a group of over 20 chimpanzees residing at the Leipzig Zoo,
Germany, with a particular focus on documenting the developmental trajectory of
one young male, Azibo. ChimpACT is both comprehensive and challenging,
consisting of 163 videos with a cumulative 160,500 frames, each richly
annotated with detection, identification, pose estimation, and fine-grained
spatiotemporal behavior labels. We benchmark representative methods of three
tracks on ChimpACT: (i) tracking and identification, (ii) pose estimation, and
(iii) spatiotemporal action detection of the chimpanzees. Our experiments
reveal that ChimpACT offers ample opportunities for both devising new methods
and adapting existing ones to solve fundamental computer vision tasks applied
to chimpanzee groups, such as detection, pose estimation, and behavior
analysis, ultimately deepening our comprehension of communication and sociality
in non-human primates.Comment: NeurIPS 202
Structural Insights into the Evolution of a Non-Biological Protein: Importance of Surface Residues in Protein Fold Optimization
Phylogenetic profiling of amino acid substitution patterns in proteins has led many to conclude that most structural information is carried by interior core residues that are solvent inaccessible. This conclusion is based on the observation that buried residues generally tolerate only conserved sequence changes, while surface residues allow more diverse chemical substitutions. This notion is now changing as it has become apparent that both core and surface residues play important roles in protein folding and stability. Unfortunately, the ability to identify specific mutations that will lead to enhanced stability remains a challenging problem. Here we discuss two mutations that emerged from an in vitro selection experiment designed to improve the folding stability of a non-biological ATP binding protein. These mutations alter two solvent accessible residues, and dramatically enhance the expression, solubility, thermal stability, and ligand binding affinity of the protein. The significance of both mutations was investigated individually and together, and the X-ray crystal structures of the parent sequence and double mutant protein were solved to a resolution limit of 2.8 and 1.65 Ã…, respectively. Comparative structural analysis of the evolved protein to proteins found in nature reveals that our non-biological protein evolved certain structural features shared by many thermophilic proteins. This experimental result suggests that protein fold optimization by in vitro selection offers a viable approach to generating stable variants of many naturally occurring proteins whose structures and functions are otherwise difficult to study