Papers by Rollyn Labuguen
Frontiers in Behavioral Neuroscience, 2021
Video-based markerless motion capture permits quantification of an animal's pose and motion, ... more Video-based markerless motion capture permits quantification of an animal's pose and motion, with a high spatiotemporal resolution in a naturalistic context, and is a powerful tool for analyzing the relationship between the animal's behaviors and its brain functions. Macaque monkeys are excellent non-human primate models, especially for studying neuroscience. Due to the lack of a dataset allowing training of a deep neural network for the macaque's markerless motion capture in the naturalistic context, it has been challenging to apply this technology for macaques-based studies. In this study, we created MacaquePose, a novel open dataset with manually labeled body part positions (keypoints) for macaques in naturalistic scenes, consisting of >13,000 images. We also validated the application of the dataset by training and evaluating an artificial neural network with the dataset. The results indicated that the keypoint estimation performance of the trained network was clos...
This paper proposes a system for pose estimation on monkeys, in diverse and challenging scenarios... more This paper proposes a system for pose estimation on monkeys, in diverse and challenging scenarios, and under complex social interactions by using OpenPose. In comparison to most animals used for research, Monkeys present additional difficulties for pose estimation. Multiple degrees of freedom, unique complex postures, intricated social interactions, among others. Our monkey OpenPose trained model is robust against these difficulties. It achieves similar performance as in human pose estimation models, and it can run in Realtime.
Understanding animal behavior in its natural habitat is a challenging task. One of the primary st... more Understanding animal behavior in its natural habitat is a challenging task. One of the primary step for analyzing animal behavior is feature detection. In this study, we propose the use of deep convolutional neural network (CNN) to locate monkey features from raw RGB images of monkey in its natural environment. We train the model to identify features such as the nose and shoulders of the monkey at about 0.01 model loss.
2012 IEEE 8th International Colloquium on Signal Processing and its Applications, 2012
This paper presents an automated fish fry counting by detecting the pixel area occupied by each f... more This paper presents an automated fish fry counting by detecting the pixel area occupied by each fish silhouette using image processing. A photo of the fish fry in a specially designed container undergoes binarization and edge detection. For every image frame, the total fish count is the sum of the area inside every contour. Then the average number of fishes
bioRxiv, 2020
The evaluation of markerless pose estimation performed by OpenPose has been getting much attentio... more The evaluation of markerless pose estimation performed by OpenPose has been getting much attention from researchers of human movement studies. This work aims to evaluate and compare the output joint positions estimated by the OpenPose with a marker-based motion-capture data recorded on a pop dance motion. Although the marker-based motion capture can accurately measure and record the human joint positions, this particular set-up is expensive. The framework to compare the outputs of the markerless method to the ground truth marker-based joint remains unknown, especially for complex body motion. Synchronization, camera calibration, and 3D reconstruction by fusing the outputs of the markerless method (OpenPose) are discussed. In this case study, the comparison results illustrate that even if the markerless method expects to fail when the subject’s body parts are self-occluded, the average magnitude errors for each key points are less than 700 mm.
2018 Joint 7th International Conference on Informatics, Electronics & Vision (ICIEV) and 2018 2nd International Conference on Imaging, Vision & Pattern Recognition (icIVPR), 2018
In this paper, we propose a visualization framework for mouse anatomical cardinal planes and axes... more In this paper, we propose a visualization framework for mouse anatomical cardinal planes and axes by extending an open-source platform called "3DTracker-FAB" and demonstrate its capability towards augmentation. Previously, the 3DTracker-FAB was only able to determine the mouse anatomical model, showing its head, neck, trunk, hip, and nose. We enhance the software to include body axes and planes of the subject in relation to its anatomical model. This work will help scientist working with animals since anatomical axis and planes are used for describing motion, and anatomical location.
Human temporal lobe epilepsy (TLE), which has convulsions, occurs after brain injury and the late... more Human temporal lobe epilepsy (TLE), which has convulsions, occurs after brain injury and the latent period. The detection of epileptic development using a prevention system may inhibit the occurrence of TLE symptoms. However, behavior modification that predicts the activity of epilepsy is poorly confirmed in both human and animal models. In this study, we used rats, which have simple neural circuits compared to humans, and demonstrated animal behavior modification at the latent period. We administrated a glutamate receptor agonist kainate and established an acute epilepsy model. Subsequently, we tested the kainate-treatment behavior modification, trajectory, and elevated plus maze test at the latent period. Consequently, self-grooming, locomotor activity, total locomotor distance, and the rate of locomotor distance with a running speed faster than 35 cm/s in the Kainate group were significantly higher than those in the Control group. In addition, the open-arm staying time, and the o...
2019 Joint 8th International Conference on Informatics, Electronics & Vision (ICIEV) and 2019 3rd International Conference on Imaging, Vision & Pattern Recognition (icIVPR)
2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)
This paper discusses the use of a low-cost unmanned aerial vehicle (UAV)-based remote sensing sys... more This paper discusses the use of a low-cost unmanned aerial vehicle (UAV)-based remote sensing system for different applications, namely post-disaster assessment, environmental management and monitoring of infrastructure development. A collaborative research consortium was established to promote the acquisition, post processing, analysis and sharing of UAV-based aerial imagery. A streamlined workflow -flight planning and data acquisition, post-processing, data delivery and collaborative sharing -was created in order to deliver acquired images and orthorectified maps to various stakeholders within this consortium. Various use case examples of UAV aerial imagery work are still in ongoing development. Initial experience shows that the combination of aerial surveys, ground observations and collaborative sharing with domain experts results in richer information content and a more effective decision support system.
2015 IEEE Tenth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), 2015
TENCON 2012 IEEE Region 10 Conference, 2012
ABSTRACT Visibility measurements are useful in areas such as air traffic control, air pollutant m... more ABSTRACT Visibility measurements are useful in areas such as air traffic control, air pollutant monitoring, urban traffic monitoring, vehicle safety, and also rain monitoring. Instead of using transmissometers and nephelometers, a simple off the shelf camera was deployed on the 11th floor of a multi-tenant building to sample a scene with a wide depth of field. The camera was automated to take pictures once per minute for seven days during and after a typhoon. Selected daytime events were processed. Three different patches of varying distances from the camera were processed for 6 different channels (RGB and HSV) for the entire duration using 6 different criteria - mean, column contrast, row contrast, gradient mean, spectral norm, and information entropy. In a separate deployment over the same area, an acoustic sensor was deployed on the field that corresponds to one patch in the image. It was demonstrated that the contrasts move together with the gradient, the spectral norms move together with the mean, while the saturation entropy has an inverse relationship with the contrast as well as the mean. It was also demonstrated that the envelope of the RGB mean follows the envelope for the acoustic sensor.
Procedia Environmental Sciences, 2014
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Papers by Rollyn Labuguen