77 research outputs found
CaloriNet: From silhouettes to calorie estimation in private environments
We propose a novel deep fusion architecture, CaloriNet, for the online
estimation of energy expenditure for free living monitoring in private
environments, where RGB data is discarded and replaced by silhouettes. Our
fused convolutional neural network architecture is trainable end-to-end, to
estimate calorie expenditure, using temporal foreground silhouettes alongside
accelerometer data. The network is trained and cross-validated on a publicly
available dataset, SPHERE_RGBD + Inertial_calorie. Results show
state-of-the-art minimum error on the estimation of energy expenditure
(calories per minute), outperforming alternative, standard and single-modal
techniques.Comment: 11 pages, 7 figure
Quantifying Facial Age by Posterior of Age Comparisons
We introduce a novel approach for annotating large quantity of in-the-wild
facial images with high-quality posterior age distribution as labels. Each
posterior provides a probability distribution of estimated ages for a face. Our
approach is motivated by observations that it is easier to distinguish who is
the older of two people than to determine the person's actual age. Given a
reference database with samples of known ages and a dataset to label, we can
transfer reliable annotations from the former to the latter via
human-in-the-loop comparisons. We show an effective way to transform such
comparisons to posterior via fully-connected and SoftMax layers, so as to
permit end-to-end training in a deep network. Thanks to the efficient and
effective annotation approach, we collect a new large-scale facial age dataset,
dubbed `MegaAge', which consists of 41,941 images. Data can be downloaded from
our project page mmlab.ie.cuhk.edu.hk/projects/MegaAge and
github.com/zyx2012/Age_estimation_BMVC2017. With the dataset, we train a
network that jointly performs ordinal hyperplane classification and posterior
distribution learning. Our approach achieves state-of-the-art results on
popular benchmarks such as MORPH2, Adience, and the newly proposed MegaAge.Comment: To appear on BMVC 2017 (oral) revised versio
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