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Multi-view Body Part Recognition with Random Forests
Published on Apr 03, 20143082 Views
This paper addresses the problem of human pose estimation, given images taken from multiple dynamic but calibrated cameras. We consider solving this task using a part-based model and focus on the pa
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Chapter list
Multi-view Body Part Recognition with Random Forests00:00
Problem 00:09
The Typical 3D Pose Data Set00:17
Our New 3D Pose Data Set00:29
2D & 3D Pose Estimation using Pictorial Structures/Part-based Models01:01
Pictorial Structures & Part-based Models - 101:27
Pictorial Structures & Part-based Models - 202:09
Part Appearance Model02:41
2D Part Appearance Model02:49
Body Part Classification as 2D Appearance Model03:01
Decision Tree for Pixel Classification03:35
Random Forest04:18
Depth of trees and number of trees04:23
2D Pose Estimation Demo Movie04:43
3D Part Appearance Model - 105:37
3D Part Appearance Model - 205:59
The Problem of Symmetric Body Parts - 106:33
The Problem of Symmetric Body Parts - 206:42
The Problem of Symmetric Body Parts - 306:52
Aggregating Scores Across Views07:17
Naive Multi-view Pose Estimation08:03
The Problem of Symmetric Body Parts - 408:27
Handle Left-Right Correspondences with a Latent Variable09:01
Multi-view Inference09:34
3D Part Appearance Model10:15
Multi-view Pose Estimation10:42
Conclusions - 111:29
Conclusions - 211:42
Conclusions - 311:50
Thank you!12:07