Answers.Body: <p>There are two important parts:</p>
  
  <ul>
  <li>When you track, you have a trajectory you can expect. So it becomes easier to "look into the future" is you understand the past</li>
  <li>When you loose an object you had a trajectory of before, you might be able to come up with an explanation that can influence your behavior</li>
  </ul>
  
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Answers.CreationDate: 2018-11-10T12:13:53.190Z
Answers.LastActivityDate: 2018-11-10T12:13:53.190Z
Answers.UserDisplayName: Martin Thoma
Answers.Body: <p>Offline tracking requires knowlege of the future of an object.</p>
  
  <p>For real time applications such as the ones you cited, offline tracking might be impeditive given that the method needs to wait for future frames.</p>
  
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Answers.CreationDate: 2019-03-23T22:05:20.000Z
Answers.LastActivityDate: 2019-03-23T22:05:20.000Z
Answers.UserDisplayName: Pedro Henrique Monforte
Body: <p>Objects tracking is finding the trajectory of each object in consecutive frames. Human tracking is a subset of object tracking which just considers humans.</p>
  
  <p>I've seen many papers that divide tracking methods into two parts: </p>
  
  <ol>
  <li>Online tracking: Tracker just uses current and previous frames.</li>
  <li>Offline tracking: Tracker uses all frames.</li>
  </ol>
  
  <p>All of them mention that online tracking is suitable for autonomous driving and robotics, but I don't understand this part. What are the applications of object/human tracking in autonomous driving? </p>
  
  <p>Do you know some related papers?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2018-09-07T17:59:05.267Z
Comments.Text: Many good questions generate some degree of opinion based on expert experience, but answers to this question will tend to be almost entirely based on opinions, rather than facts, references, or specific expertise. If this question can be reworded to fit the rules in the help center
Comments.UserDisplayName: quintumnia
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2018-09-07T18:13:38.457Z
Comments.Text: It purely depends on which algorithm the self-driving car is using.  But what exactly do you mean by human tracking?  A lot of modern self-driving cars use the YOLO (you only look once) algorithm for object detection.  So at each sampling time, it looks at the surroundings of the car and identify objects, such as humans.
Comments.UserDisplayName: Rui Nian
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2018-09-07T18:21:04.880Z
Comments.Text: @RuiNian Object detection determines different objects and their location in a frame, Object tracking/Human tracking determines trajectory(Path) of objects/humans in consecutive frames. 
  
  I have seen many papers that mention online tracking is useful for autonomous driving. But I don't understand how tracking is useful for autonomous driving.
Comments.UserDisplayName: CVDE
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2018-09-07T18:30:27.490Z
Comments.Text: I personally don't have a lot of industry experience with self driving cars, but the reason for tracking in other control problems is for trajectory optimization.  Traditionally, predictive controls are used to forecast the trajectories of dynamic states (person in this case) in the environment so the controller (the car in this case) can behave optimally in the most probabilistic scenario.  For example, if a person is biking at 50 km/h across a street, there is a high chance he is going to cross the street, so the car must behave differently than if there was no biker.
Comments.UserDisplayName: Rui Nian
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2018-09-07T18:30:29.897Z
Comments.Text: Online trajectory optimization is very high computational cost, so I believe most trajectory optimizations for cars are done using offline methods, and the models are put online.  I know the UC Berkeley self driving car team does this.
Comments.UserDisplayName: Rui Nian
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2018-09-07T18:39:10.840Z
Comments.Text: @quintumnia I edited the question.
Comments.UserDisplayName: CVDE
Tags: <computer-vision><autonomous-vehicles>
Title: What are applications of object/human tracking in autonomous cars?
UserDisplayName: CVDE
ThreadText: # What are applications of object/human tracking in autonomous cars?
  
  (Asked by: username_0 on 2018-09-07)
  
  Objects tracking is finding the trajectory of each object in consecutive frames. Human tracking is a subset of object tracking which just considers humans.
  
  I've seen many papers that divide tracking methods into two parts:
  
  1. Online tracking: Tracker just uses current and previous frames.
  2. Offline tracking: Tracker uses all frames.
  
  All of them mention that online tracking is suitable for autonomous driving and robotics, but I don't understand this part. What are the applications of object/human tracking in autonomous driving?
  
  Do you know some related papers?
  
  **Tags:** computer-vision, autonomous-vehicles
  
  > **Comments:**
  > **username_1**: Many good questions generate some degree of opinion based on expert experience, but answers to this question will tend to be almost entirely based on opinions, rather than facts, references, or specific expertise. If this question can be reworded to fit the rules in the help center  
  > **username_2**: It purely depends on which algorithm the self-driving car is using.  But what exactly do you mean by human tracking?  A lot of modern self-driving cars use the YOLO (you only look once) algorithm for object detection.  So at each sampling time, it looks at the surroundings of the car and identify objects, such as humans.  
  > **username_0**: @username_2 Object detection determines different objects and their location in a frame, Object tracking/Human tracking determines trajectory(Path) of objects/humans in consecutive frames.   I have seen many papers that mention online tracking is useful for autonomous driving. But I don't understand how tracking is useful for autonomous driving.  
  > **username_2**: I personally don't have a lot of industry experience with self driving cars, but the reason for tracking in other control problems is for trajectory optimization.  Traditionally, predictive controls are used to forecast the trajectories of dynamic states (person in this case) in the environment so the controller (the car in this case) can behave optimally in the most probabilistic scenario.  For example, if a person is biking at 50 km/h across a street, there is a high chance he is going to cross the street, so the car must behave differently than if there was no biker.  
  > **username_2**: Online trajectory optimization is very high computational cost, so I believe most trajectory optimizations for cars are done using offline methods, and the models are put online.  I know the UC Berkeley self driving car team does this.  
  > **username_0**: @username_1 I edited the question.  
  
  ---
  
  ## 2 answers
  
  ### Answer by username_3 on 2018-11-10. Score: 1 | Accepted answer
  
  There are two important parts:
  
  * When you track, you have a trajectory you can expect. So it becomes easier to "look into the future" is you understand the past
  * When you loose an object you had a trajectory of before, you might be able to come up with an explanation that can influence your behavior
  
  
  ---
  
  ### Answer by username_4 on 2019-03-23. Score: 0
  
  Offline tracking requires knowlege of the future of an object.
  
  For real time applications such as the ones you cited, offline tracking might be impeditive given that the method needs to wait for future frames.
  
  
  ---
  
  