• Single Target Tracking (Bee)

    published: 16 Aug 2012
  • Indoor single target tracking

    This video demonstrates single target tracking using a 24 node RF sensor network.

    published: 29 Apr 2012
  • Occlusion Handling in Single Target Tracking

    An occlusion handling method based on Spatio-temporal Oriented Energy (SOE) features, for improving the tracking performance in occlusion events

    published: 10 Jul 2015
  • Single Target Tracking #3

    Tracking with single target

    published: 18 Apr 2013
  • Inside, single target tracking with NCC

    Both the NCC with Kalman filter and and the NCC with Kalman filter and template updates results

    published: 14 Dec 2015
  • Auto & Manual Motion Tracking an Object with Premiere Pro

    KEYFRAME BY KEYFRAME TRACKING AND THE SINGLE CLICK TRACKING! | We will check out how to make a call out title follow a moving object in this video. 💰 Buy the Photoshop Course and Support the Channelhttp://bit.ly/28NuwFy 🏆 My Instagram: http://instagram.com/tutvid 🎯 Subscribe for Daily Tutorials → https://goo.gl/DN4Nln – In this Premier Pro video editing tutorial, we will use keyframes to manually keyframe out call out title along with a moving object in this video clip and use a series of clicks that will make the best of a situation that isn’t yet automated in Premiere Pro. We will then create a mask to pixelate out somebody’s face and use the auto-tracking feature to use the power of Premiere’s engine to generate as many keyframes as needed to auto track an object in your video. ...

    published: 13 Sep 2017
  • How to play with Reap Souls on Single Target

    :)

    published: 05 Oct 2017
  • Single-target tracking mcRBM

    Target tracking with the proposed model for tracking. A 9-gaze template is chosen in order to model the appearance and the shape of the target (i.e., a hockey player). The learned policy converges to the gaze G4. The tracker is not hijacked by the other similar players.

    published: 02 Feb 2011
  • Global Data Association for Multiple Pedestrian Tracking

    Final Oral Examination of: Afshin Dehghan For the Degree of: Doctor of Philosophy (Computer Science) Firstly, a new framework for multi-target tracking that uses a novel data association technique employing the Generalized Maximum Clique Problem (GMCP) formulation is presented. The majority of current methods, such as bipartite matching, incorporate a limited temporal locality of the sequence into the data association problem. On the other hand, our approach incorporates both motion and appearance in a global manner. The proposed method incorporates the whole temporal span and solves the data association problem for one object at a time. GMCP is used to solve the optimization problem of our data association. GMCP leads us to a more accurate approach to multi-object tracking; however, it...

    published: 26 Apr 2016
  • ADVANCED RIFLE NEVER MISSES it's target. Tracking Point Rifle unveiled in Austin Texas

    TrackingPoint is an Austin, Texas-based applied technology company that created the first precision guided firearm (PGF), a long-range rifle system.[1][2] LEARN HOW TO GET YOUR FEDERAL FIREARMS LICENCE CLICK HERE http://13e4933lo3ir8kba07mdg-6ixz.hop.clickbank.net/ TrackingPoint was formed by CEO John McHale in February 2011. The first PGF prototype was created in March 2011. The company officially launched a publicly available product in January 2013.[3] TrackingPoint's precision guided firearms system uses several component technologies: Networked Tracking Scope: The core engine that tracks the target, calculates range and the ballistic solution, and works in concert with the shooter and guided trigger to release the shot.[4][5] Barrel Reference System: A fixed reference point that ena...

    published: 26 Oct 2013
  • Single Agent Topology for Target Tracking SD

    Link to Publication: http://robotics.usc.edu/~muellerj/publications/papers/hausman14iser.pdf

    published: 23 Jan 2015
  • Radar Demo Doppler Single Target

    published: 30 Mar 2017
  • Maneuvering Target Tracking Demo

    published: 05 Jul 2011
  • Continuous Energy Minimization for Multi-Target Tracking

    A supplemental video for the following IEEE PAMI article Continuous Energy Minimization for Multitarget Tracking A. Milan, S. Roth and K. Schindler IEEE Trans. Pattern Anal. Mach. Intell. 36(1): 58-72 (2014)

    published: 08 Oct 2013
  • Deep Learning for Multi-Target Tracking

    published: 27 Apr 2016
  • Target Identity-aware Network Flow for Online Multiple Target Tracking

    Afshin Dehghan presents TINF tracker Authors: Afshin Dehghan, Yicong Tian, Philip. H. S. Torr, Mubarak Shah, in Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR 2015) homepage:http://crcv.ucf.edu/people/phd_students/afshin/

    published: 04 Jun 2015
  • MULTIPLE vs SINGLE INFERNO TOWER! - Clash of Clans

    Whats the difference between the single target and the multi target inferno tower? Well thats what im gonna be explaining in this video! I will be demonstrating it by attacking my friends base to show you the pros and the cons of both settings of the inferno tower. Then i will tell you guys my favorite setting. I hope you guys enjoy this video and thanks for watching! Twitter: @AM_Blitz Previous video: https://www.youtube.com/watch?v=cvVMYsXj3wU You can check out Cinch Gaming at: https://cinchgaming.com You can also check out NoScope at: https://www.noscopeglasses.com/gaming-glasses?tracking=amblitz Music: Instrumental produced by Chuki. His youtube - http://www.youtube.com/user/CHUKImusic My shop on Storenvy will be coming soon!! - Jaden...

    published: 01 Dec 2016
  • Single Target Tracking in Clutter - With and Without Learning - Uniform Update Rate

    In this simulation, we perform single target tracking. A measurement is received every 11 time steps. With the results shown in the left panel, we have trained the learner over 2000 time steps. The results shown in the right panel do not benefit from learning. Both panels use a gated Kalman filter as the tracker. The current state estimate is shown in red. Measurements at the current time step are shown in green. Measurements from the past 25 time steps are shown in blue.

    published: 24 Dec 2014
  • Single-target tracking mcRBM

    Target tracking with the proposed model for tracking. A 3-gaze template is chosen in order to model the appearance and the shape of the target (i.e., a pedestrian). The learned policy converges to the first gaze, corresponding to the upper part of the human body.

    published: 02 Feb 2011
  • Stable Multi-Target Tracking in Real-Time Surveillance Video (CVPR 2011)

    The video demonstrates a stable head tracking system that can run at 25fps on 1920x1080 video using a standard desktop computer. The system is capable of obtaining stable head images and is robust to temporary occlusions. For more information, see the following page: http://www.robots.ox.ac.uk/ActiveVision/Publications/benfold_reid_cvpr2011/benfold_reid_cvpr2011.html

    published: 21 Apr 2011
  • Radar Demo 3D Single Target

    published: 30 Mar 2017
  • Demo on a Single Ground-based Target Tracking using Spectral Features and Grayscale images

    published: 02 Mar 2015
  • Tracking Moving Objects Using Kalman Filter

    This is the presentation of my project.

    published: 08 Dec 2013
  • Sensor Fusion for Object Tracking

    Tracking in modern commercial VR systems is based on the principle of sensor fusion, where measurements from multiple independent sensors are combined to estimate the position and orientation of tracked objects with better quality than what can be achieved by using those same sensors in isolation. This video shows a simulation of a moving and rotating object in two dimensions, tracked by an external absolute measurement system and a relative measurement system integrated into the tracked object. Measurements from these two systems are combined using a non-linear extension of the Kalman filter, yielding a result with low noise, low update latency, and no drift. Related videos: Pure IMU-based Positional Tracking is a No-go: https://www.youtube.com/watch?v=_q_8d0E3tDk Optical 3D Pose Estima...

    published: 02 Sep 2017
developed with YouTube
Single Target Tracking (Bee)
0:15

Single Target Tracking (Bee)

  • Order:
  • Duration: 0:15
  • Updated: 16 Aug 2012
  • views: 1076
videos
https://wn.com/Single_Target_Tracking_(Bee)
Indoor single target tracking
0:44

Indoor single target tracking

  • Order:
  • Duration: 0:44
  • Updated: 29 Apr 2012
  • views: 251
videos
This video demonstrates single target tracking using a 24 node RF sensor network.
https://wn.com/Indoor_Single_Target_Tracking
Occlusion Handling in Single Target Tracking
0:08

Occlusion Handling in Single Target Tracking

  • Order:
  • Duration: 0:08
  • Updated: 10 Jul 2015
  • views: 117
videos
An occlusion handling method based on Spatio-temporal Oriented Energy (SOE) features, for improving the tracking performance in occlusion events
https://wn.com/Occlusion_Handling_In_Single_Target_Tracking
Single Target Tracking #3
0:09

Single Target Tracking #3

  • Order:
  • Duration: 0:09
  • Updated: 18 Apr 2013
  • views: 17
videos
Tracking with single target
https://wn.com/Single_Target_Tracking_3
Inside, single target tracking with NCC
0:12

Inside, single target tracking with NCC

  • Order:
  • Duration: 0:12
  • Updated: 14 Dec 2015
  • views: 89
videos
Both the NCC with Kalman filter and and the NCC with Kalman filter and template updates results
https://wn.com/Inside,_Single_Target_Tracking_With_Ncc
Auto & Manual Motion Tracking an Object with Premiere Pro
8:25

Auto & Manual Motion Tracking an Object with Premiere Pro

  • Order:
  • Duration: 8:25
  • Updated: 13 Sep 2017
  • views: 156781
videos
KEYFRAME BY KEYFRAME TRACKING AND THE SINGLE CLICK TRACKING! | We will check out how to make a call out title follow a moving object in this video. 💰 Buy the Photoshop Course and Support the Channelhttp://bit.ly/28NuwFy 🏆 My Instagram: http://instagram.com/tutvid 🎯 Subscribe for Daily Tutorials → https://goo.gl/DN4Nln – In this Premier Pro video editing tutorial, we will use keyframes to manually keyframe out call out title along with a moving object in this video clip and use a series of clicks that will make the best of a situation that isn’t yet automated in Premiere Pro. We will then create a mask to pixelate out somebody’s face and use the auto-tracking feature to use the power of Premiere’s engine to generate as many keyframes as needed to auto track an object in your video. ⚡️ written tutorial here: http://bit.ly/2f4k1ac INSTAGRAM: http://instagram.com/tutvid TWITTER: http://twitter.com/tutvid FACEBOOK: https://www.facebook.com/tutvid SNAPCHAT: tutvid.com tutvid is a YouTube channel dedicated to creating the best Adobe Photoshop, Premiere Pro, Lightroom, and Illustrator tutorials. My goal is to create the best, most informative, and entertaining tutorials on the web. If you enjoy my videos, the best way to support what I do here is to purchase my course linked above or simply subscribe to the YouTube channel by pressing the red button. ✉️ business inquiries: nate@tutvid.com –
https://wn.com/Auto_Manual_Motion_Tracking_An_Object_With_Premiere_Pro
How to play with Reap Souls on Single Target
4:55

How to play with Reap Souls on Single Target

  • Order:
  • Duration: 4:55
  • Updated: 05 Oct 2017
  • views: 4821
videos
:)
https://wn.com/How_To_Play_With_Reap_Souls_On_Single_Target
Single-target tracking mcRBM
1:26

Single-target tracking mcRBM

  • Order:
  • Duration: 1:26
  • Updated: 02 Feb 2011
  • views: 647
videos
Target tracking with the proposed model for tracking. A 9-gaze template is chosen in order to model the appearance and the shape of the target (i.e., a hockey player). The learned policy converges to the gaze G4. The tracker is not hijacked by the other similar players.
https://wn.com/Single_Target_Tracking_Mcrbm
Global Data Association for Multiple Pedestrian Tracking
44:17

Global Data Association for Multiple Pedestrian Tracking

  • Order:
  • Duration: 44:17
  • Updated: 26 Apr 2016
  • views: 4423
videos
Final Oral Examination of: Afshin Dehghan For the Degree of: Doctor of Philosophy (Computer Science) Firstly, a new framework for multi-target tracking that uses a novel data association technique employing the Generalized Maximum Clique Problem (GMCP) formulation is presented. The majority of current methods, such as bipartite matching, incorporate a limited temporal locality of the sequence into the data association problem. On the other hand, our approach incorporates both motion and appearance in a global manner. The proposed method incorporates the whole temporal span and solves the data association problem for one object at a time. GMCP is used to solve the optimization problem of our data association. GMCP leads us to a more accurate approach to multi-object tracking; however, it has some limitations. Firstly, it finds target trajectories one-by-one, missing joint optimization. Secondly, for optimization we use a greedy solver, making GMCP prone to local minima. Finally GMCP tracker is slow. In order to address these problems, we propose a new graph theoretic problem formulation called Generalized Maximum Multi Clique Problem (GMMCP). GMMCP has all the advantages of the GMCP tracker while addressing its limitations. Previous works assume simplified version of the ideal tracking scenario either in problem formulation or problem optimization. However, we propose a solution to GMMCP where no simplification is assumed in either steps. We show that, GMMCP can be solved efficiently through Binary-Integer Program while guaranteeing the optimal solution. We further propose a speed-up method which reduces the size of input graph without assuming any heuristic. Thus far we have assumed that the number of people do not exceed a few dozen. However, this is not always the case. In many scenarios such as, marathons, political rallies or religious rites, the number of people in a frame may reach few hundreds or even few thousands. Human detection methods often fail to localize objects in extremely crowded scenes. This limits the use of data association based tracking methods, including GMCP and GMMCP. Finally, we formulate online crowd tracking as a Binary Quadratic Programing, where both detection and data association problems are solved together. Our tracker brings in both target’s individual information and contextual cues into a single objective function. Due to large number of targets, state-of-the-art commercial quadratic programing solvers fail to efficiently find the solution to proposed optimization. In order to overcome the computational complexity of available solvers, we propose to use the most recent version of Modified Frank-Wolfe algorithm. The proposed tracker can track hundreds of targets efficiently and improve state-of-the-art results by significant margin.
https://wn.com/Global_Data_Association_For_Multiple_Pedestrian_Tracking
ADVANCED RIFLE NEVER MISSES it's target. Tracking Point Rifle unveiled in Austin Texas
1:37

ADVANCED RIFLE NEVER MISSES it's target. Tracking Point Rifle unveiled in Austin Texas

  • Order:
  • Duration: 1:37
  • Updated: 26 Oct 2013
  • views: 1499986
videos
TrackingPoint is an Austin, Texas-based applied technology company that created the first precision guided firearm (PGF), a long-range rifle system.[1][2] LEARN HOW TO GET YOUR FEDERAL FIREARMS LICENCE CLICK HERE http://13e4933lo3ir8kba07mdg-6ixz.hop.clickbank.net/ TrackingPoint was formed by CEO John McHale in February 2011. The first PGF prototype was created in March 2011. The company officially launched a publicly available product in January 2013.[3] TrackingPoint's precision guided firearms system uses several component technologies: Networked Tracking Scope: The core engine that tracks the target, calculates range and the ballistic solution, and works in concert with the shooter and guided trigger to release the shot.[4][5] Barrel Reference System: A fixed reference point that enables the networked tracking scope to make adjustments and retain zero over time. The barrel reference system is factory calibrated to a laser reference.[6] Guided Trigger: The rifle's trigger is hard-wired to the networked tracking scope. The networked tracking scope controls the trigger weight to eliminate trigger squeeze and shot timing errors.[7] Field Software Upgradeable: Software can be uploaded to the scope to add capability.[8] Heads Up Display (HUD): The HUD indicates range, wind, reticle, video storage gauge, zoom, and battery life, plus LRF icon, Wi-Fi on/off icon, compass icon, cant wheel, inclination wheels and off-screen indicators.[4][9] Recording: An integrated camera captures video and still images from the networked tracking scope and heads up display. Recorded images can be downloaded to a smartphone or tablet from the scope and transmitted via email or social media.[10] A rifle is a firearm designed to be fired from the shoulder, with a barrel that has a helical groove or pattern of grooves ("rifling") cut into the barrel walls. The raised areas of the rifling are called "lands," which make contact with the projectile (for small arms usage, called a bullet), imparting spin around an axis corresponding to the orientation of the weapon. When the projectile leaves the barrel, this spin lends gyroscopic stability to the projectile and prevents tumbling, in the same way that a properly thrown American football or rugby ball behaves. This allows the use of aerodynamically-efficient pointed bullets (as opposed to the spherical balls used in muskets) and thus improves range and accuracy. The word "rifle" originally referred to the grooving, and a rifle was called a "rifled gun." Rifles are used in warfare, hunting and shooting sports. Typically, a bullet is propelled by the contained deflagration of an explosive compound (originally black powder, later cordite, and now nitrocellulose), although other means such as compressed air are used in air rifles, which are popular for vermin control, hunting small game, formal target shooting and casual shooting ("plinking"). In most armed forces the term "gun" is incorrect when referring to small arms; in military parlance, the word "gun" refers to an artillery piece or crew-served machine gun. Furthermore, in many works of fiction a rifle refers to any weapon that has a stock and is shouldered before firing, even if the weapon is not rifled or does not fire solid projectiles (e.g. a "laser rifle"). A gun is a normally tubular weapon or other device designed to discharge projectiles or other material.[1] The projectile may be solid, liquid, gas or energy and may be free, as with bullets and artillery shells, or captive as with Taser probes and whaling harpoons. The means of projection varies according to design but is usually effected by the action of gas pressure, either produced through the rapid combustion of a propellant or compressed and stored by mechanical means, operating on the projectile inside an open-ended tube in the fashion of a piston. The confined gas accelerates the movable projectile down the length of the tube imparting sufficient velocity to sustain the projectile's travel once the action of the gas ceases at the end of the tube or muzzle. Alternatively, acceleration via electromagnetic field generation may be employed in which case the tube may be dispensed with and a guide rail substituted. The first devices identified as guns appeared in China around 1000AD, and by the 12th century the technology was spreading through the rest of Asia, and into Europe by the 13th century.[2] Texas is the second most populous, after California, and the second-largest of the 50 states, after Alaska in the United States of America, and the largest state in the 48 contiguous United States. Geographically located in the South Central part of the country, Texas shares an international border with the Mexican states of Chihuahua, Coahuila, Nuevo León, and Tamaulipas to the south and borders the U.S. states of New Mexico to the west, Oklahoma to the north, Arkansas to the northeast, and Louisiana to the east. Texas has an area of 268,820 square miles (696,200 km2) and
https://wn.com/Advanced_Rifle_Never_Misses_It's_Target._Tracking_Point_Rifle_Unveiled_In_Austin_Texas
Single Agent Topology for Target Tracking SD
2:14

Single Agent Topology for Target Tracking SD

  • Order:
  • Duration: 2:14
  • Updated: 23 Jan 2015
  • views: 69
videos
Link to Publication: http://robotics.usc.edu/~muellerj/publications/papers/hausman14iser.pdf
https://wn.com/Single_Agent_Topology_For_Target_Tracking_Sd
Radar Demo   Doppler Single Target
0:22

Radar Demo Doppler Single Target

  • Order:
  • Duration: 0:22
  • Updated: 30 Mar 2017
  • views: 167
videos
https://wn.com/Radar_Demo_Doppler_Single_Target
Maneuvering Target Tracking Demo
2:54

Maneuvering Target Tracking Demo

  • Order:
  • Duration: 2:54
  • Updated: 05 Jul 2011
  • views: 140
videos
https://wn.com/Maneuvering_Target_Tracking_Demo
Continuous Energy Minimization for Multi-Target Tracking
1:42

Continuous Energy Minimization for Multi-Target Tracking

  • Order:
  • Duration: 1:42
  • Updated: 08 Oct 2013
  • views: 2167
videos
A supplemental video for the following IEEE PAMI article Continuous Energy Minimization for Multitarget Tracking A. Milan, S. Roth and K. Schindler IEEE Trans. Pattern Anal. Mach. Intell. 36(1): 58-72 (2014)
https://wn.com/Continuous_Energy_Minimization_For_Multi_Target_Tracking
Deep Learning for Multi-Target Tracking
0:55

Deep Learning for Multi-Target Tracking

  • Order:
  • Duration: 0:55
  • Updated: 27 Apr 2016
  • views: 975
videos
https://wn.com/Deep_Learning_For_Multi_Target_Tracking
Target Identity-aware Network Flow for Online Multiple Target Tracking
18:46

Target Identity-aware Network Flow for Online Multiple Target Tracking

  • Order:
  • Duration: 18:46
  • Updated: 04 Jun 2015
  • views: 2093
videos
Afshin Dehghan presents TINF tracker Authors: Afshin Dehghan, Yicong Tian, Philip. H. S. Torr, Mubarak Shah, in Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR 2015) homepage:http://crcv.ucf.edu/people/phd_students/afshin/
https://wn.com/Target_Identity_Aware_Network_Flow_For_Online_Multiple_Target_Tracking
MULTIPLE vs SINGLE INFERNO TOWER! - Clash of Clans
8:11

MULTIPLE vs SINGLE INFERNO TOWER! - Clash of Clans

  • Order:
  • Duration: 8:11
  • Updated: 01 Dec 2016
  • views: 28621
videos
Whats the difference between the single target and the multi target inferno tower? Well thats what im gonna be explaining in this video! I will be demonstrating it by attacking my friends base to show you the pros and the cons of both settings of the inferno tower. Then i will tell you guys my favorite setting. I hope you guys enjoy this video and thanks for watching! Twitter: @AM_Blitz Previous video: https://www.youtube.com/watch?v=cvVMYsXj3wU You can check out Cinch Gaming at: https://cinchgaming.com You can also check out NoScope at: https://www.noscopeglasses.com/gaming-glasses?tracking=amblitz Music: Instrumental produced by Chuki. His youtube - http://www.youtube.com/user/CHUKImusic My shop on Storenvy will be coming soon!! - Jaden
https://wn.com/Multiple_Vs_Single_Inferno_Tower_Clash_Of_Clans
Single Target Tracking in Clutter - With and Without Learning - Uniform Update Rate
1:07

Single Target Tracking in Clutter - With and Without Learning - Uniform Update Rate

  • Order:
  • Duration: 1:07
  • Updated: 24 Dec 2014
  • views: 56
videos
In this simulation, we perform single target tracking. A measurement is received every 11 time steps. With the results shown in the left panel, we have trained the learner over 2000 time steps. The results shown in the right panel do not benefit from learning. Both panels use a gated Kalman filter as the tracker. The current state estimate is shown in red. Measurements at the current time step are shown in green. Measurements from the past 25 time steps are shown in blue.
https://wn.com/Single_Target_Tracking_In_Clutter_With_And_Without_Learning_Uniform_Update_Rate
Single-target tracking mcRBM
0:58

Single-target tracking mcRBM

  • Order:
  • Duration: 0:58
  • Updated: 02 Feb 2011
  • views: 217
videos
Target tracking with the proposed model for tracking. A 3-gaze template is chosen in order to model the appearance and the shape of the target (i.e., a pedestrian). The learned policy converges to the first gaze, corresponding to the upper part of the human body.
https://wn.com/Single_Target_Tracking_Mcrbm
Stable Multi-Target Tracking in Real-Time Surveillance Video (CVPR 2011)
1:11

Stable Multi-Target Tracking in Real-Time Surveillance Video (CVPR 2011)

  • Order:
  • Duration: 1:11
  • Updated: 21 Apr 2011
  • views: 157740
videos
The video demonstrates a stable head tracking system that can run at 25fps on 1920x1080 video using a standard desktop computer. The system is capable of obtaining stable head images and is robust to temporary occlusions. For more information, see the following page: http://www.robots.ox.ac.uk/ActiveVision/Publications/benfold_reid_cvpr2011/benfold_reid_cvpr2011.html
https://wn.com/Stable_Multi_Target_Tracking_In_Real_Time_Surveillance_Video_(Cvpr_2011)
Radar Demo   3D Single Target
0:37

Radar Demo 3D Single Target

  • Order:
  • Duration: 0:37
  • Updated: 30 Mar 2017
  • views: 140
videos
https://wn.com/Radar_Demo_3D_Single_Target
Demo on a Single Ground-based Target Tracking using Spectral Features and Grayscale images
0:22

Demo on a Single Ground-based Target Tracking using Spectral Features and Grayscale images

  • Order:
  • Duration: 0:22
  • Updated: 02 Mar 2015
  • views: 66
videos
https://wn.com/Demo_On_A_Single_Ground_Based_Target_Tracking_Using_Spectral_Features_And_Grayscale_Images
Tracking Moving Objects Using Kalman Filter
10:57

Tracking Moving Objects Using Kalman Filter

  • Order:
  • Duration: 10:57
  • Updated: 08 Dec 2013
  • views: 8819
videos
This is the presentation of my project.
https://wn.com/Tracking_Moving_Objects_Using_Kalman_Filter
Sensor Fusion for Object Tracking
24:56

Sensor Fusion for Object Tracking

  • Order:
  • Duration: 24:56
  • Updated: 02 Sep 2017
  • views: 6027
videos
Tracking in modern commercial VR systems is based on the principle of sensor fusion, where measurements from multiple independent sensors are combined to estimate the position and orientation of tracked objects with better quality than what can be achieved by using those same sensors in isolation. This video shows a simulation of a moving and rotating object in two dimensions, tracked by an external absolute measurement system and a relative measurement system integrated into the tracked object. Measurements from these two systems are combined using a non-linear extension of the Kalman filter, yielding a result with low noise, low update latency, and no drift. Related videos: Pure IMU-based Positional Tracking is a No-go: https://www.youtube.com/watch?v=_q_8d0E3tDk Optical 3D Pose Estimation of Oculus Rift DK2: https://www.youtube.com/watch?v=X4G6_zt1qKY Lighthouse Tracking Examined - Headset at Rest: https://www.youtube.com/watch?v=Uzv2H3PDPDg Lighthouse Tracking Examined - Headset in Motion: https://www.youtube.com/watch?v=XwxwMruEE7Y Lighthouse Tracking Examined - Controller in Motion: https://www.youtube.com/watch?v=A75uKqA67FI Playstation Move Tracking Test: https://www.youtube.com/watch?v=0J5LaWykiIU More information: https://en.wikipedia.org/wiki/Kalman_filter
https://wn.com/Sensor_Fusion_For_Object_Tracking
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