• 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 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
  • Single Target Tracking #3

    Tracking with single target

    published: 18 Apr 2013
  • 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
  • Indoor single target tracking

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

    published: 29 Apr 2012
  • Single Target Tracking (Bee)

    published: 16 Aug 2012
  • 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
  • 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
  • Stationary Target Tracking Using Double Pendulum - Single Motor

    There is just a single motor connecting the first arm to the base of the pendulum

    published: 29 Jan 2015
  • 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
  • Tracking a Single Target

    A single vehicle is tracked by an airborne camera. The target is identified by its color distribution, and a bounding box surrounds the estimated position of the target in the image. The corners of the bounding box are used as feature points in the tracking algorithm, which regulates the sample mean and variance of the points in the image to keep the target in view.

    published: 27 Aug 2009
  • Deep Learning for Multi-Target Tracking

    published: 27 Apr 2016
  • Maneuvering Target Tracking Demo

    published: 05 Jul 2011
  • auto target tracking test

    published: 19 Oct 2015
  • Visual Object Tracking using Powell's Direct Set Method and Kalman Filtering

    This video contains the results of a tracking algorithm which I have proposed in my thesis for MS degree at Military College of Signals, NUST, Pakistan. Thesis Abstract: Visual object tracking is defined as the task of locating an object as it moves around in a video sequence. It has widespread applications in the area of human-computer interaction, security and surveillance, video communication and compression, augmented reality, traffic control and medical imaging. Amongst all the trackers, kernel based trackers have gained popularity in the recent past because of their simplicity and robustness to track a variety of objects. However, such trackers usually encode only single view of the object and face problems due to changing appearance patterns of the object, non-rigid object structu...

    published: 23 Jan 2013
  • USB Turret Test - Single Target Track

    Single Target Track mode testing for autonomous paintball turret software.

    published: 27 Aug 2008
Occlusion Handling in Single Target Tracking

Occlusion Handling in Single Target Tracking

  • Order:
  • Duration: 0:08
  • Updated: 10 Jul 2015
  • views: 96
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 mcRBM

Single-target tracking mcRBM

  • Order:
  • Duration: 0:58
  • Updated: 02 Feb 2011
  • views: 211
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
Single Target Tracking #3

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
Single-target tracking mcRBM

Single-target tracking mcRBM

  • Order:
  • Duration: 1:26
  • Updated: 02 Feb 2011
  • views: 575
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
Indoor single target tracking

Indoor single target tracking

  • Order:
  • Duration: 0:44
  • Updated: 29 Apr 2012
  • views: 238
videos
This video demonstrates single target tracking using a 24 node RF sensor network.
https://wn.com/Indoor_Single_Target_Tracking
Single Target Tracking (Bee)

Single Target Tracking (Bee)

  • Order:
  • Duration: 0:15
  • Updated: 16 Aug 2012
  • views: 930
videos
https://wn.com/Single_Target_Tracking_(Bee)
Inside, single target tracking with NCC

Inside, single target tracking with NCC

  • Order:
  • Duration: 0:12
  • Updated: 14 Dec 2015
  • views: 65
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
Single Target Tracking in Clutter - With and Without Learning - Uniform Update Rate

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

  • Order:
  • Duration: 1:07
  • Updated: 24 Dec 2014
  • views: 48
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
Stationary Target Tracking Using Double Pendulum  - Single Motor

Stationary Target Tracking Using Double Pendulum - Single Motor

  • Order:
  • Duration: 1:03
  • Updated: 29 Jan 2015
  • views: 10
videos
There is just a single motor connecting the first arm to the base of the pendulum
https://wn.com/Stationary_Target_Tracking_Using_Double_Pendulum_Single_Motor
Global Data Association for Multiple Pedestrian Tracking

Global Data Association for Multiple Pedestrian Tracking

  • Order:
  • Duration: 44:17
  • Updated: 26 Apr 2016
  • views: 2641
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
Tracking a Single Target

Tracking a Single Target

  • Order:
  • Duration: 0:31
  • Updated: 27 Aug 2009
  • views: 242
videos
A single vehicle is tracked by an airborne camera. The target is identified by its color distribution, and a bounding box surrounds the estimated position of the target in the image. The corners of the bounding box are used as feature points in the tracking algorithm, which regulates the sample mean and variance of the points in the image to keep the target in view.
https://wn.com/Tracking_A_Single_Target
Deep Learning for Multi-Target Tracking

Deep Learning for Multi-Target Tracking

  • Order:
  • Duration: 0:55
  • Updated: 27 Apr 2016
  • views: 450
videos
https://wn.com/Deep_Learning_For_Multi_Target_Tracking
Maneuvering Target Tracking Demo

Maneuvering Target Tracking Demo

  • Order:
  • Duration: 2:54
  • Updated: 05 Jul 2011
  • views: 119
videos
https://wn.com/Maneuvering_Target_Tracking_Demo
auto target tracking test

auto target tracking test

  • Order:
  • Duration: 2:43
  • Updated: 19 Oct 2015
  • views: 727
videos
https://wn.com/Auto_Target_Tracking_Test
Visual Object Tracking using Powell's Direct Set Method and Kalman Filtering

Visual Object Tracking using Powell's Direct Set Method and Kalman Filtering

  • Order:
  • Duration: 2:47
  • Updated: 23 Jan 2013
  • views: 7325
videos
This video contains the results of a tracking algorithm which I have proposed in my thesis for MS degree at Military College of Signals, NUST, Pakistan. Thesis Abstract: Visual object tracking is defined as the task of locating an object as it moves around in a video sequence. It has widespread applications in the area of human-computer interaction, security and surveillance, video communication and compression, augmented reality, traffic control and medical imaging. Amongst all the trackers, kernel based trackers have gained popularity in the recent past because of their simplicity and robustness to track a variety of objects. However, such trackers usually encode only single view of the object and face problems due to changing appearance patterns of the object, non-rigid object structures, object-to-object and object-to-scene occlusions, and camera motion. In this research, a new kernel-based method for real-time tracking of objects seen from a moving or static camera is proposed with an object to resolve these problems. In contrast to brute-force search, this method uses Powell's gradient ascent method to optimally find the most likely target position in every frame. Moreover, a template adaption module has also been proposed which accounts for the changes in shape, size, orientation and shading conditions of the target object over time. The proposed algorithm also handles short-term partial and full occlusion by using Kalman filter for trajectory prediction and Proximity Search for relocking object once it reappears in the scene after occlusion. The performance of proposed algorithm has been evaluated on a number of publicly available real-world sequences. Experimental results show robust performance of tracker for objects with changing appearance and undergoing short-term and long-term full occlusion. The computational complexity of the tracker is exceptionally low, thus making it suitable for real-time applications.
https://wn.com/Visual_Object_Tracking_Using_Powell's_Direct_Set_Method_And_Kalman_Filtering
USB Turret Test - Single Target Track

USB Turret Test - Single Target Track

  • Order:
  • Duration: 0:24
  • Updated: 27 Aug 2008
  • views: 373
videos
Single Target Track mode testing for autonomous paintball turret software.
https://wn.com/Usb_Turret_Test_Single_Target_Track
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