• Title/Summary/Keyword: Animal tracking

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DEVELOPMENT OF THE HAUSAT-2 PAYLOAD OF ANIMAL TRACKING SYSTEM (HAUSAT-2 소형 위성 동물 추적 시스템 탑재체 개발)

  • Lee Jeong-Nam;Lee Byung-Hoon;Moon Byung-Young;Chang Young-Keun
    • Bulletin of the Korean Space Science Society
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    • 2006.04a
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    • pp.129-132
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    • 2006
  • Animal Tracking System consists of Animal Tracking System Receiver on the Satellite segment, Animal Tracking Terminal and Ground Station for data analysis on the Ground segment. This paper describes operation concept and hardware design for Animal Tracking System which is the payload of HAUSAT-2 being developed by the Space System Research Laboratory (SSRL). Algorithms for determination of animal position and data processing are also referred to.

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Animal Tracking in Infrared Video based on Adaptive GMOF and Kalman Filter

  • Pham, Van Khien;Lee, Guee Sang
    • Smart Media Journal
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    • v.5 no.1
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    • pp.78-87
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    • 2016
  • The major problems of recent object tracking methods are related to the inefficient detection of moving objects due to occlusions, noisy background and inconsistent body motion. This paper presents a robust method for the detection and tracking of a moving in infrared animal videos. The tracking system is based on adaptive optical flow generation, Gaussian mixture and Kalman filtering. The adaptive Gaussian model of optical flow (GMOF) is used to extract foreground and noises are removed based on the object motion. Kalman filter enables the prediction of the object position in the presence of partial occlusions, and changes the size of the animal detected automatically along the image sequence. The presented method is evaluated in various environments of unstable background because of winds, and illuminations changes. The results show that our approach is more robust to background noises and performs better than previous methods.

Development of Cost-Effective Platform for Tracking and Analysis of Animal Ambulatory Patterns

  • Kwon, Jeonghoon;Park, Hong Ju;Joo, Segyeong;Huh, Soo-Jin
    • Journal of Sensor Science and Technology
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    • v.23 no.2
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    • pp.82-86
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    • 2014
  • This paper reports the development of a platform for tracking and analysis of animal locomotion. The platform is composed of a commercial webcam, a metal stand for the webcam, and a plastic bathtub as a cage. Using it, researchers can track and analyze an animal's movement within the plastic bathtub's dimensions of $100cm{\times}100cm{\times}55cm$ in a cost-effective manner. After recording the locomotion of an animal with $1920{\times}1080$ resolution at a rate of 30 frames per second, finding the position of the animal in each frame and analyzing the ambulation pattern were executed with custom software. To evaluate the performance of the platform, movements of imprinting control region mice and transgenic mice were recorded and analyzed. The analysis successfully compared velocity, moving pattern, and total moving distance for the two mouse groups. In addition, the developed platform can be used not only in simple motion analysis but also in various experimental conditions, such as a water maze, by easy customization of the platform. Such a simple and cost-effective platform yields a powerful tool for animal ambulatory analysis.

The Present Status of Cell Tracking Methods in Animal Models Using Magnetic Resonance Imaging Technology

  • Kim, Daehong;Hong, Kwan Soo;Song, Jihwan
    • Molecules and Cells
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    • v.23 no.2
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    • pp.132-137
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    • 2007
  • With the advance of stem cell transplantation research, in vivo cell tracking techniques have become increasingly important in recent years. Magnetic resonance imaging (MRI) may provide a unique tool for non-invasive tracking of transplanted cells. Since the initial findings on the stem cell migration by MRI several years ago, there have been numerous studies using various animal models, notably in heart or brain disease models. In order to develop more reliable and clinically applicable methodologies, multiple aspects should be taken into consideration. In this review, we will summarize the current status and future perspectives of in vivo cell tracking technologies using MRI. In particular, use of different MR contrast agents and their detection methods using MRI will be described in much detail. In addition, various cell labeling methods to increase the sensitivity of signals will be extensively discussed. We will also review several key experiments, in which MRI techniques were utilized to detect the presence and/or migration of transplanted stem cells in various animal models. Finally, we will discuss the current problems and future directions of cell tracking methods using MRI.

A Tracking Service of Animal Situation using RFID, GPS, and Sensor (RFID, GPS 및 센서를 이용한 동물 상태 추적 서비스)

  • Kim, So-Hyeun;Kim, Do-Hyeun;Park, Hee-Dong
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.9 no.5
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    • pp.79-84
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    • 2009
  • Recently, many researches are being carried out on monitoring animal behaviour and interactions with the environment using sensor networks and for tracing animal chain management and identifying animals using RFID techniques. And we are studying about the management and burglarproof of a pet using GPS technique. But there is a lack of study for providing users intelligence services in zoo using GPS, RFID, and sensor networks. Accordingly, in this paper, we propose a intelligence tracking service of animal situation based on GPS, RFID, and sensor in zoo. Firstly, we present a tracking service scenario of animal situation and system configuration according to this scenario. The proposed service provides users realtime animal situation information of animal like the present location, temperature, image, etc. In addition, we can chase the animals to know a location and situation of animal when the animals escapes from their cages. Next, we implement and test prototype operations of animal tracking system based on this scenario to verify the proposed service.

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Two-dimensional speckle-tracking of antral contraction in dogs

  • Park, Junghyun;An, Soyon;Hwang, Tae Sung;Lee, Hee Chun
    • Korean Journal of Veterinary Research
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    • v.60 no.2
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    • pp.55-59
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    • 2020
  • This study was purposed to make the referenced range of stomach antral contraction strain in 50 dogs using 2-dimensional speckle tracking. In addition, the strain results were compared among body condition scores to reveal the correlations of obesity among the subjects of the study. Finally, the medetomidine group that was comprised of 10 dogs was compared with the normal group to identify the medetomidine pharmacologic effect in the stomach antral contraction. Clinically healthy 50 dogs were recruited for the study. In an ultrasonographic examination, the stomach antrum region was scanned, and at least one cycle of antral contraction was recorded. The peak strain of antral contraction in healthy dogs was 58.2 ± 20.47% (mean ± SD). The obesity group showed a high strain result and there were significant correlations between the body condition score (BCS) 2, BCS 3 groups and BCS 8 group. The medetomidine group revealed a low strain result and was significantly correlated with normal group. Two-dimensional speckle tracking was useful to the evaluation of stomach motility disorders.

Multi-Cattle tracking with appearance and motion models in closed barns using deep learning

  • Han, Shujie;Fuentes, Alvaro;Yoon, Sook;Park, Jongbin;Park, Dong Sun
    • Smart Media Journal
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    • v.11 no.8
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    • pp.84-92
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    • 2022
  • Precision livestock monitoring promises greater management efficiency for farmers and higher welfare standards for animals. Recent studies on video-based animal activity recognition and tracking have shown promising solutions for understanding animal behavior. To achieve that, surveillance cameras are installed diagonally above the barn in a typical cattle farm setup to monitor animals constantly. Under these circumstances, tracking individuals requires addressing challenges such as occlusion and visual appearance, which are the main reasons for track breakage and increased misidentification of animals. This paper presents a framework for multi-cattle tracking in closed barns with appearance and motion models. To overcome the above challenges, we modify the DeepSORT algorithm to achieve higher tracking accuracy by three contributions. First, we reduce the weight of appearance information. Second, we use an Ensemble Kalman Filter to predict the random motion information of cattle. Third, we propose a supplementary matching algorithm that compares the absolute cattle position in the barn to reassign lost tracks. The main idea of the matching algorithm assumes that the number of cattle is fixed in the barn, so the edge of the barn is where new trajectories are most likely to emerge. Experimental results are performed on our dataset collected on two cattle farms. Our algorithm achieves 70.37%, 77.39%, and 81.74% performance on HOTA, AssA, and IDF1, representing an improvement of 1.53%, 4.17%, and 0.96%, respectively, compared to the original method.

Object Tracking Algorithm for Intelligent Robot using Sound Source Tracking Sensor Network (음원 센서네트워크를 이용한 지능형 로봇의 목표물 추적 알고리즘)

  • Jang, In-Hun;Park, Kyoung-Jin;Yang, Hyun-Chang;Lee, Jong-Chang;Sim, Kwee-Bo
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.10
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    • pp.983-989
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    • 2007
  • Most of life thing including human being have tendency of reaction with inherently their own pattern against environmental change caused by such as light, sound, smell etc. Especially, a sense of direction often works as a very important factor in such reaction. Actually, human or animal lift that can react instantly to a stimulus determine their action with a sense of direction to a stimulant. In this paper, we try to propose how to give a sense of direction to a robot using sound being representative stimulant, and tracking sensors being able to detect the direction of such sound source. We also try to propose how to determine the relative directions among devices or robots using the digital compass and the RSSI on wireless network.

Animal Tracking System Using the Doppler Effect for Single LEO Satellite (도플러 효과를 이용한 단일 저궤도위성의 동물추적시스템 개발)

  • Lee, Jeong-Nam;Jang, Yeong-Geun;Lee, Byeong-Hun;Mun, Byeong-Yeong
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.34 no.11
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    • pp.61-69
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    • 2006
  • Position determination accuracy is strongly depending on how much precisely and frequently satellite receiver measures transmitted signals from terminals on target animals when Doppler effect is applied for position determination. ARGOS satellite system has shown relatively high position determination accuracy by operating multiple satellites, which enable operator to get more Doppler shift data from terminals. In case of animal tracking mission with single satellite, however, it is difficult for the satellite receiver to receive transmitted signals from terminals frequently during short period that satellite passes over ground terminals. This is one of the main sources to decrease position accuracy on target animals. In this paper, the Doppler rate estimation is implemented to increase the number of Doppler shift data received by single satellite. It is proved that the relatively high position determination accuracy with increased number of estimated data can be obtained. We also suggest that the Doppler rate estimation is applicable for position determination system with single satellite.

Object detection and tracking using a high-performance artificial intelligence-based 3D depth camera: towards early detection of African swine fever

  • Ryu, Harry Wooseuk;Tai, Joo Ho
    • Journal of Veterinary Science
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    • v.23 no.1
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    • pp.17.1-17.10
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    • 2022
  • Background: Inspection of livestock farms using surveillance cameras is emerging as a means of early detection of transboundary animal disease such as African swine fever (ASF). Object tracking, a developing technology derived from object detection aims to the consistent identification of individual objects in farms. Objectives: This study was conducted as a preliminary investigation for practical application to livestock farms. With the use of a high-performance artificial intelligence (AI)-based 3D depth camera, the aim is to establish a pathway for utilizing AI models to perform advanced object tracking. Methods: Multiple crossovers by two humans will be simulated to investigate the potential of object tracking. Inspection of consistent identification will be the evidence of object tracking after crossing over. Two AI models, a fast model and an accurate model, were tested and compared with regard to their object tracking performance in 3D. Finally, the recording of pig pen was also processed with aforementioned AI model to test the possibility of 3D object detection. Results: Both AI successfully processed and provided a 3D bounding box, identification number, and distance away from camera for each individual human. The accurate detection model had better evidence than the fast detection model on 3D object tracking and showed the potential application onto pigs as a livestock. Conclusions: Preparing a custom dataset to train AI models in an appropriate farm is required for proper 3D object detection to operate object tracking for pigs at an ideal level. This will allow the farm to smoothly transit traditional methods to ASF-preventing precision livestock farming.