Relevant bibliographies by topics / Camera based Depth Estimation

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Camera based Depth Estimation'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Camera based Depth Estimation"

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Lin, Bor-Shing, I.-Jung Lee, Chin-Shyurng Fahn, Yi-Fang Lee, Wei-Jen Chou, and Meng-Luen Wu. "Depth-Camera Based Energy Expenditure Estimation System for Physical Activity Using Posture Classification Algorithm." Sensors 21, no. 12 (2021): 4216. http://dx.doi.org/10.3390/s21124216.

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Insufficient physical activity is common in modern society. By estimating the energy expenditure (EE) of different physical activities, people can develop suitable exercise plans to improve their lifestyle quality. However, several limitations still exist in the related works. Therefore, the aim of this study is to propose an accurate EE estimation model based on depth camera data with physical activity classification to solve the limitations in the previous research. To decide the best location and amount of cameras of the EE estimation, three depth cameras were set at three locations, namely
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Mansour, Mostafa, Pavel Davidson, Oleg Stepanov, and Robert Piché. "Relative Importance of Binocular Disparity and Motion Parallax for Depth Estimation: A Computer Vision Approach." Remote Sensing 11, no. 17 (2019): 1990. http://dx.doi.org/10.3390/rs11171990.

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Binocular disparity and motion parallax are the most important cues for depth estimation in human and computer vision. Here, we present an experimental study to evaluate the accuracy of these two cues in depth estimation to stationary objects in a static environment. Depth estimation via binocular disparity is most commonly implemented using stereo vision, which uses images from two or more cameras to triangulate and estimate distances. We use a commercial stereo camera mounted on a wheeled robot to create a depth map of the environment. The sequence of images obtained by one of these two came
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Furmonas, Justas, John Liobe, and Vaidotas Barzdenas. "Analytical Review of Event-Based Camera Depth Estimation Methods and Systems." Sensors 22, no. 3 (2022): 1201. http://dx.doi.org/10.3390/s22031201.

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Event-based cameras have increasingly become more commonplace in the commercial space as the performance of these cameras has also continued to increase to the degree where they can exponentially outperform their frame-based counterparts in many applications. However, instantiations of event-based cameras for depth estimation are sparse. After a short introduction detailing the salient differences and features of an event-based camera compared to that of a traditional, frame-based one, this work summarizes the published event-based methods and systems known to date. An analytical review of the
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Son, Eunjin, Jiho Choi, Jimin Song, Yongsik Jin, and Sang Jun Lee. "Monocular Depth Estimation from a Fisheye Camera Based on Knowledge Distillation." Sensors 23, no. 24 (2023): 9866. http://dx.doi.org/10.3390/s23249866.

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Monocular depth estimation is a task aimed at predicting pixel-level distances from a single RGB image. This task holds significance in various applications including autonomous driving and robotics. In particular, the recognition of surrounding environments is important to avoid collisions during autonomous parking. Fisheye cameras are adequate to acquire visual information from a wide field of view, reducing blind spots and preventing potential collisions. While there have been increasing demands for fisheye cameras in visual-recognition systems, existing research on depth estimation has pri
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Seo, Jonghyun, and Jangmyung Lee. "Object-Based Visual Servoing for Autonomous Mobile Manipulators." International Journal of Humanoid Robotics 11, no. 03 (2014): 1450025. http://dx.doi.org/10.1142/s021984361450025x.

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This paper proposes an object based vision (O-BV) system to implement visual servoing for autonomous mobile manipulators using two charge-coupled device (CCD) cameras. Conventional stereo vision (C-SV) system estimates the depth based on the disparity between two camera images for the same object. However, the disparity is not an effective cue for a small disparity at a long distance. To resolve this problem, in the proposed O-BV system, the individual camera tracks the object independently, and the angles of the two cameras are used to estimate the distance to the object. This depth estimatio
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Zaman, DMS, Md Hasan Maruf, Md Ashiqur Rahman, Jannatul Ferdousy, and ASM Shihavuddin. "Food Depth Estimation Using Low-Cost Mobile-Based System for Real-Time Dietary Assessment." GUB Journal of Science and Engineering 6, no. 1 (2020): 1–11. http://dx.doi.org/10.3329/gubjse.v6i1.52044.

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Real time estimation of nutrition intake from regular food items using mobile-based applications could be a breakthrough in creating public awareness of threats in overeating or faulty food choices. The bottleneck in implementing such systems is to effectively estimate the depths of the food items which is essential to calculate the volumes of foods. Volumes and density of food items can be used to estimate the weights of food eaten and their corresponding nutrition contents. Without specific depth sensors, it is very difficult to estimate the depth of any object from a single camera. Such sen
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Shimada, Tomoyasu, Hiroki Nishikawa, Xiangbo Kong, and Hiroyuki Tomiyama. "Pix2Pix-Based Monocular Depth Estimation for Drones with Optical Flow on AirSim." Sensors 22, no. 6 (2022): 2097. http://dx.doi.org/10.3390/s22062097.

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In this work, we propose a method for estimating depth for an image of a monocular camera in order to avoid a collision for the autonomous flight of a drone. The highest flight speed of a drone is generally approximate 22.2 m/s, and long-distant depth information is crucial for autonomous flights since if the long-distance information is not available, the drone flying at high speeds is prone to collisions. However, long-range, measurable depth cameras are too heavy to be equipped on a drone. This work applies Pix2Pix, which is a kind of Conditional Generative Adversarial Nets (CGAN). Pix2Pix
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Wu, Zhihong, Fuxiang Li, Yuan Zhu, Ke Lu, and Mingzhi Wu. "Design of a Robust System Architecture for Tracking Vehicle on Highway Based on Monocular Camera." Sensors 22, no. 9 (2022): 3359. http://dx.doi.org/10.3390/s22093359.

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Multi-Target tracking is a central aspect of modeling the environment of autonomous vehicles. A mono camera is a necessary component in the autonomous driving system. One of the biggest advantages of the mono camera is it can give out the type of vehicle and cameras are the only sensors able to interpret 2D information such as road signs or lane markings. Besides this, it has the advantage of estimating the lateral velocity of the moving object. The mono camera is now being used by companies all over the world to build autonomous vehicles. In the expressway scenario, the forward-looking camera
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Ma, Lan, and Hua Huo. "2D to 3D Human Skeleton Estimation Based on the Brown Camera Distortion Model and Constrained Optimization." Electronics 14, no. 5 (2025): 960. https://doi.org/10.3390/electronics14050960.

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In the rapidly evolving field of computer vision and machine learning, 3D skeleton estimation is critical for applications such as motion analysis and human–computer interaction. While stereo cameras are commonly used to acquire 3D skeletal data, monocular RGB systems attract attention due to benefits including cost-effectiveness and simple deployment. However, persistent challenges remain in accurately inferring depth from 2D images and reconstructing 3D structures using monocular approaches. The current 2D to 3D skeleton estimation methods overly rely on deep training of datasets, while negl
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Kaichi, Tomoya, Tsubasa Maruyama, Mitsunori Tada, and Hideo Saito. "Resolving Position Ambiguity of IMU-Based Human Pose with a Single RGB Camera." Sensors 20, no. 19 (2020): 5453. http://dx.doi.org/10.3390/s20195453.

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Human motion capture (MoCap) plays a key role in healthcare and human–robot collaboration. Some researchers have combined orientation measurements from inertial measurement units (IMUs) and positional inference from cameras to reconstruct the 3D human motion. Their works utilize multiple cameras or depth sensors to localize the human in three dimensions. Such multiple cameras are not always available in our daily life, but just a single camera attached in a smart IP devices has recently been popular. Therefore, we present a 3D pose estimation approach from IMUs and a single camera. In order to
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Dissertations / Theses on the topic "Camera based Depth Estimation"

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Januzi, Altin. "Triple-Camera Setups for Image-Based Depth Estimation." Thesis, Uppsala universitet, Institutionen för elektroteknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-422717.

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This study was conducted as to attempt to find whether a three-camera setup could improve depth map retrieval as opposed to a two-camera setup. The study is based on three main ideas to exploit information from the additional camera. These are three cameras on one axis, as to exploit wide and short baseline benefits, three cameras on different axes, as to exploit vertical and horizontal scanning of the scene and a third idea of combining the two previous ideas. More than three cameras would impose particular implications on the solution and without sufficient theoretical justification thereof
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Nassir, Cesar. "Domain-Independent Moving Object Depth Estimation using Monocular Camera." Thesis, KTH, Robotik, perception och lärande, RPL, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-233519.

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Today automotive companies across the world strive to create vehicles with fully autonomous capabilities. There are many benefits of developing autonomous vehicles, such as reduced traffic congestion, increased safety and reduced pollution, etc. To be able to achieve that goal there are many challenges ahead, one of them is visual perception. Being able to estimate depth from a 2D image has been shown to be a key component for 3D recognition, reconstruction and segmentation. Being able to estimate depth in an image from a monocular camera is an ill-posed problem since there is ambiguity betwee
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Shafaei, Alireza. "Multiview depth-based pose estimation." Thesis, University of British Columbia, 2015. http://hdl.handle.net/2429/56180.

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Commonly used human motion capture systems require intrusive attachment of markers that are visually tracked with multiple cameras. In this work we present an efficient and inexpensive solution to markerless motion capture using only a few Kinect sensors. We use our system to design a smart home platform with a network of Kinects that are installed inside the house. Our first contribution is a multiview pose estimation system. Unlike the previous work on 3d pose estimation using a single depth camera, we relax constraints on the camera location and do not assume a co-operative user. We
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Huotari, V. (Ville). "Depth camera based customer behaviour analysis for retail." Master's thesis, University of Oulu, 2015. http://urn.fi/URN:NBN:fi:oulu-201510292099.

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In 2000s traditional shop-based retailing has had to adapt to competition created by internet-based e-commerce. As a distinction from traditional retail, e-commerce can gather unprecedented amount of information about its customers and their behaviour. To enable behaviour-based analysis in traditional retailing, the customers need to be tracked reliably through the store. One such tracking technology is depth camera people tracking system developed at VTT, Technical Research Centre of Finland Ltd. This study aims to use the aforementioned people tracking system’s data to enable e-commerce sty
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Harding, Cressida M. "How far away is it? : depth estimation by a moving camera." Thesis, University of Canterbury. Electrical and Electronic Engineering, 2001. http://hdl.handle.net/10092/6157.

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This thesis considers the challenge of autonomous robot navigation. Effective self-guiding robots are a tool applicable to many important and critical tasks, such as fire-fighting, transporting dangerous materials, even bomb disposal. In many cases the robots are even more useful if their method of guidance is passive and utilises common technology such as CCD cameras. Using biological models to inspire the design of such robots is an exhilarating approach to the problem and provides sensible and novel solutions. The method of determining distance to objects using the optical flow from sequen
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Sun, Yi. "Depth Estimation Methodology for Modern Digital Photography." University of Cincinnati / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1563527854489549.

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Aldrovandi, Lorenzo. "Depth estimation algorithm for light field data." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018.

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Sandberg, David. "Model-Based Video Coding Using a Colour and Depth Camera." Thesis, Linköpings universitet, Datorseende, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-68737.

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In this master thesis, a model-based video coding algorithm has been developed that uses input from a colour and depth camera, such as the Microsoft Kinect. Using a model-based representation of a video has several advantages over the commonly used block-based approach, used by the H.264 standard. For example, videos can be rendered in 3D, be viewed from alternative views, and have objects inserted into them for augmented reality and user interaction. This master thesis demonstrates a very efficient way of encoding the geometry of a scene. The results of the proposed algorithm show that it can
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Bodesund, Fredrik. "Pose estimation of a VTOL UAV using IMU, Camera and GPS." Thesis, Linköpings universitet, Reglerteknik, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-60641.

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When an autonomous vehicle has a mission to perform, it is of high importance that the robot has good knowledge about its position. Without good knowledge of the position, it will not be able to navigate properly and the data that it gathers, which could be of importance for the mission, might not be usable. A helicopter could for example be used to collect laser data from the terrain beneath it, which could be used to produce a 3D map of the terrain. If the knowledge about the position and orientation of the helicopter is poor then the collected laser data will be useless since it is unknown
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Bartosch, Nadine. "Correspondence-based pairwise depth estimation with parallel acceleration." Thesis, Mittuniversitetet, Avdelningen för informationssystem och -teknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-34372.

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This report covers the implementation and evaluation of a stereo vision corre- spondence-based depth estimation algorithm on a GPU. The results and feed- back are used for a Multi-view camera system in combination with Jetson TK1 devices for parallelized image processing and the aim of this system is to esti- mate the depth of the scenery in front of it. The performance of the algorithm plays the key role. Alongside the implementation, the objective of this study is to investigate the advantages of parallel acceleration inter alia the differences to the execution on a CPU which are significant
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Books on the topic "Camera based Depth Estimation"

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Vision-Based Pedestrian Detection and Estimation with a Blind Corner Camera. GRIN Verlag GmbH, 2013.

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Morozova, Katerina. Parameter Estimation on Hybrid Zenith Camera and Gravimeter Data for Integrated Gravity Field and Geoid Determination Based on Spherical-cap-harmonics Modelling. RTU Press, 2022. http://dx.doi.org/10.7250/9789934228179.

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The main objective of the Doctoral Thesis is to develop a new solution for the Earth gravity field determination based on spherical-cap-harmonic modelling, using both vertical deflection and gravimetric hybrid data. The values of vertical deflections caused by gravity field anomaly are computed using digital zenith camera. It is a new kind of astrogeodetic instrument employing recent advancements in several areas of technology. The intention is to use vertical deflections along with GNSS/levelling and gravity data to improve the local quasi-geoid model including both physical and geometrical d
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Book chapters on the topic "Camera based Depth Estimation"

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Westendorf, M., S. Thal, T. Ahrenhold, and R. Henze. "Accuracy Requirements of Camera-Based Depth Estimation for Urban Automated Driving." In Lecture Notes in Mechanical Engineering. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-70392-8_23.

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AbstractFor autonomous driving in urban areas higher accuracy requirements for localization of surrounding traffic participants become apparent. The use of cost-efficient camera sensors shows potential for a performant depth estimation and can supplement perception systems to achieve redundancy. Current research focuses on improving the algorithms towards better performance whereas the application-oriented analysis of present estimation errors in relation to urban traffic scenarios is often neglected. Based on stereo and mono camera images, a benchmark analysis of rule- and deep learning-based
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Zhang, Xingguo, Daiki Ikami, and Pongsathorn Raksincharoensak. "Robust 3D On-Road Object Detection and Distance Estimation for Active Vehicle Control Systems Based on Monocular Camera Image Data." In Lecture Notes in Mechanical Engineering. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-70392-8_65.

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Abstract3D object detection from monocular camera videos constitutes a critical research domain. Achieving robust 3D object detection in databases lacking annotated information poses a highly challenging task. This paper proposes a simple yet effective transfer learning approach, integrating data alignment, 3D object detection, and dynamic result correction. Vanishing point detection is employed to infer camera angles in diverse scenes, and preprocessing of new data is conducted by considering the camera's pitch angle and vanishing point position. Subsequently, MonoDETR are applied for depth e
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Kushwaha, Ajay Kumar, Supriya M. Khatavkar, Dhanashri Milind Biradar, and Prashant A. Chougule. "Depth Estimation and Navigation Route Planning for Mobile Robots Based on Stereo Camera." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-28975-0_15.

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Wakabayashi, Kyohei, Tetsuya Oda, Hideyuki Shimada, and Leonard Barolli. "Physique-Aware Skilled Motion Decision System Based on Depth Camera and Skeletal Estimation." In Lecture Notes on Data Engineering and Communications Technologies. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-86149-9_30.

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Fleischmann, Oliver, and Reinhard Koch. "Lens-Based Depth Estimation for Multi-focus Plenoptic Cameras." In Lecture Notes in Computer Science. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11752-2_33.

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Im, Jaehyun, Jaehoon Jung, and Joonki Paik. "Single Camera-Based Depth Estimation and Improved Continuously Adaptive Mean Shift Algorithm for Tracking Occluded Objects." In Lecture Notes in Computer Science. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24078-7_24.

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Ndayikengurukiye, Didier, and Max Mignotte. "High-Frequency Spectral Energy Map Estimation Based Gait Analysis System Using a Depth Camera for Pathology Detection." In Lecture Notes in Computer Science. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41501-7_5.

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Bakschik, Robert, Jan Ehlenbröker, and Volker Lohweg. "Building an Image Processing Pipeline for Processing Aerial Images of Precast Reinforced Concrete Elements in an Outdoor Storage Area into a Searchable Map." In Technologien für die intelligente Automation. Springer Berlin Heidelberg, 2025. https://doi.org/10.1007/978-3-662-70997-9_5.

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Zusammenfassung This paper aims to build a pipeline for processing aerial images of precast reinforced concrete elements stored in an outdoor storage area into a map which can be employed to locate concrete elements via object detection. The main focus lies on preprocessing to ease the image stitching process and avoid leveraging positional data. The aerial images are taken by wide angle cameras mounted to a gantry crane. The images are processed by using methods of monocular depth estimation, processed into a point cloud and finally ortho-rectified for stitching. The final result after stitch
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Quoc Tran, Dai, Yuntae Jeon, Seongwoo Son, Minsoo Park, and Seunghee Park. "Identifying Hazards in Construction Sites Using Deep Learning-Based Multimodal with CCTV Data." In CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality. Firenze University Press, 2023. http://dx.doi.org/10.36253/10.36253/979-12-215-0289-3.61.

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The use of closed-circuit television (CCTV) for safety monitoring is crucial for reducing accidents in construction sites. However, the majority of currently proposed approaches utilize single detection models without considering the context of CCTV video inputs. In this study, a multimodal detection, and depth map estimation algorithm utilizing deep learning is proposed. In addition, the point cloud of the test site is acquired using a terrestrial laser scanning scanner, and the detected object's coordinates are projected into global coordinates using a homography matrix. Consequently, the ef
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Quoc Tran, Dai, Yuntae Jeon, Seongwoo Son, Minsoo Park, and Seunghee Park. "Identifying Hazards in Construction Sites Using Deep Learning-Based Multimodal with CCTV Data." In CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality. Firenze University Press, 2023. http://dx.doi.org/10.36253/979-12-215-0289-3.61.

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The use of closed-circuit television (CCTV) for safety monitoring is crucial for reducing accidents in construction sites. However, the majority of currently proposed approaches utilize single detection models without considering the context of CCTV video inputs. In this study, a multimodal detection, and depth map estimation algorithm utilizing deep learning is proposed. In addition, the point cloud of the test site is acquired using a terrestrial laser scanning scanner, and the detected object's coordinates are projected into global coordinates using a homography matrix. Consequently, the ef
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Conference papers on the topic "Camera based Depth Estimation"

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Zhang, Jinchang, Praveen Kumar Reddy, Xue-Iuan Wong, Yiannis Aloimonos, and Guoyu Lu. "Embodiment: Self-Supervised Depth Estimation Based on Camera Models." In 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2024. https://doi.org/10.1109/iros58592.2024.10801343.

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Wang, Chaoqun, Yiran Qin, Zijian Kang, Ningning Ma, and Ruimao Zhang. "Toward Accurate Camera-based 3D Object Detection via Cascade Depth Estimation and Calibration." In 2024 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2024. http://dx.doi.org/10.1109/icra57147.2024.10610281.

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Fang, Cuiyun, Xunming Xue, Guoqing Deng, et al. "MCC-DEM: Multi-Scale Context Constraint-Based Depth Estimation Method for Monocular Camera." In 2024 IEEE 7th International Conference on Information Systems and Computer Aided Education (ICISCAE). IEEE, 2024. https://doi.org/10.1109/iciscae62304.2024.10761276.

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Li, Han, Yukai Ma, Yaqing Gu, Kewei Hu, Yong Liu, and Xingxing Zuo. "RadarCam-Depth: Radar-Camera Fusion for Depth Estimation with Learned Metric Scale." In 2024 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2024. http://dx.doi.org/10.1109/icra57147.2024.10610929.

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Xie, Yupeng, Sarah Fachada, Daniele Bonatto, Mehrdad Teratani, and Gauthier Lafruit. "View Synthesis: LiDAR Camera versus Depth Estimation." In WSCG'2021 - 29. International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision'2021. Západočeská univerzita v Plzni, 2021. http://dx.doi.org/10.24132/csrn.2021.3101.35.

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Depth-Image-Based Rendering (DIBR) can synthesize a virtual view image from a set of multiview images and corresponding depth maps. However, this requires an accurate depth map estimation that incurs a high compu- tational cost over several minutes per frame in DERS (MPEG-I’s Depth Estimation Reference Software) even by using a high-class computer. LiDAR cameras can thus be an alternative solution to DERS in real-time DIBR ap- plications. We compare the quality of a low-cost LiDAR camera, the Intel Realsense LiDAR L515 calibrated and configured adequately, with DERS using MPEG-I’s Reference Vi
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Xie, Yupeng, Sarah Fachada, Daniele Bonatto, Mehrdad Teratani, and Gauthier Lafruit. "View Synthesis: LiDAR Camera versus Depth Estimation." In WSCG'2021 - 29. International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision'2021. Západočeská univerzita, 2021. http://dx.doi.org/10.24132/csrn.2021.3002.35.

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Depth-Image-Based Rendering (DIBR) can synthesize a virtual view image from a set of multiview images andcorresponding depth maps. However, this requires an accurate depth map estimation that incurs a high compu-tational cost over several minutes per frame in DERS (MPEG-I’s Depth Estimation Reference Software) even byusing a high-class computer. LiDAR cameras can thus be an alternative solution to DERS in real-time DIBR ap-plications. We compare the quality of a low-cost LiDAR camera, the Intel Realsense LiDAR L515 calibrated andconfigured adequately, with DERS using MPEG-I’s Reference View Sy
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Huang, Zhengyu, Weizhi Du, and Theodore B. Norris. "Unsupervised Learning Based Focal Stack Camera Depth Estimation." In CLEO: Applications and Technology. Optica Publishing Group, 2022. http://dx.doi.org/10.1364/cleo_at.2022.jw3a.5.

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We propose an unsupervised deep learning based method to estimate depth from focal stack camera images. On the NYU-v2 dataset, our method achieves much better depth estimation accuracy compared to single-image based methods.
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Atanassov, Kalin, Sergio Goma, Vikas Ramachandra, and Todor Georgiev. "Content-based depth estimation in focused plenoptic camera." In IS&T/SPIE Electronic Imaging, edited by J. Angelo Beraldin, Geraldine S. Cheok, Michael B. McCarthy, et al. SPIE, 2011. http://dx.doi.org/10.1117/12.872667.

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Roberts, William, and Brian S. Thurow. "Correlation-based Depth Estimation with a Plenoptic Camera." In 54th AIAA Aerospace Sciences Meeting. American Institute of Aeronautics and Astronautics, 2016. http://dx.doi.org/10.2514/6.2016-0136.

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Nehra, Suresh, Tamal Das, Simantini Chakraborty, P. K. Biswas, and J. Mukhopadhyay. "Disparity based depth estimation using light field camera." In ICVGIP '21: Indian Conference on Computer Vision, Graphics and Image Processing. ACM, 2021. http://dx.doi.org/10.1145/3490035.3490297.

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Reports on the topic "Camera based Depth Estimation"

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Raviv, Daniel. An integration-based method for depth estimation. National Institute of Standards and Technology, 1991. http://dx.doi.org/10.6028/nist.ir.4669.

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Mesick, Hillary C., and Frank P. McCreedy. A Preliminary Investigation into the Estimation of River Depth Based on Meander Geometry. Defense Technical Information Center, 2004. http://dx.doi.org/10.21236/ada426678.

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Chitrakaran, Vilas K., and Darren M. Dawson. A Lyapunov-Based Method for Estimation of Euclidean Position of Static Features Using a Single Camera. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada462605.

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Chitrakaran, V. K., D. M. Dawson, J. Chen, and W. E. Dixon. Euclidean Position Estimation if Features on a Moving Object Using a Single Camera: A Lyapunov-Based Approach. Defense Technical Information Center, 2004. http://dx.doi.org/10.21236/ada465810.

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Fourrier, Marine. Integration of in situ and satellite multi-platform data (estimation of carbon flux for trop. Atlantic). EuroSea, 2023. http://dx.doi.org/10.3289/eurosea_d7.6.

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This report presents the results of task 7.3 on “Quantification of improvements in carbon flux data for the tropical Atlantic based on the multi-platform and neural network approach”. To better constrain changes in the ocean’s capture and sequestration of CO2 emitted by human activities, in situ measurements are needed. Tropical regions are considered to be mostly sources of CO2 to the atmosphere due to specific circulation features, with large interannual variability mainly controlled by physical drivers (Padin et al., 2010). The tropical Atlantic is the second largest source, after the tropi
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Brosh, Arieh, David Robertshaw, Yoav Aharoni, Zvi Holzer, Mario Gutman, and Amichai Arieli. Estimation of Energy Expenditure of Free Living and Growing Domesticated Ruminants by Heart Rate Measurement. United States Department of Agriculture, 2002. http://dx.doi.org/10.32747/2002.7580685.bard.

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Research objectives were: 1) To study the effect of diet energy density, level of exercise, thermal conditions and reproductive state on cardiovascular function as it relates to oxygen (O2) mobilization. 2) To validate the use of heart rate (HR) to predict energy expenditure (EE) of ruminants, by measuring and calculating the energy balance components at different productive and reproductive states. 3) To validate the use of HR to identify changes in the metabolizable energy (ME) and ME intake (MEI) of grazing ruminants. Background: The development of an effective method for the measurement of
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Liu, X., Z. Chen, and S. E. Grasby. Using shallow temperature measurements to evaluate thermal flux anomalies in the southern Mount Meager volcanic area, British Columbia, Canada. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/330009.

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Geothermal is a clean and renewable energy resource. However, locating where elevated thermal gradient anomalies exist is a significant challenge when trying to assess potential resource volumes during early exploration of a prospective geothermal area. In this study, we deployed 22 temperature probes in the shallow subsurface along the south flank of the Mount Meager volcanic complex, to measure the transient temperature variation from September 2020 to August 2021. In our data analysis, a novel approach was developed to estimate the near-surface thermal distribution, and a workflow and code
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Lee, W. S., Victor Alchanatis, and Asher Levi. Innovative yield mapping system using hyperspectral and thermal imaging for precision tree crop management. United States Department of Agriculture, 2014. http://dx.doi.org/10.32747/2014.7598158.bard.

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Original objectives and revisions – The original overall objective was to develop, test and validate a prototype yield mapping system for unit area to increase yield and profit for tree crops. Specific objectives were: (1) to develop a yield mapping system for a static situation, using hyperspectral and thermal imaging independently, (2) to integrate hyperspectral and thermal imaging for improved yield estimation by combining thermal images with hyperspectral images to improve fruit detection, and (3) to expand the system to a mobile platform for a stop-measure- and-go situation. There were no
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