real-time human motion analysis by image skeletonization

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Real-time Human Motion Analysis by Image Skeletonization. 指導教授:張元翔 老師 學生 : 9977003 吳思穎. Outline. Introduction------------------------------------------------------3 Real-time target extraction-----------------------------------5 - PowerPoint PPT Presentation

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Real-time Human Motion Analysis by Image Skeletonization

指導教授:張元翔 老師學生: 9977003 吳思穎

Outline• Introduction------------------------------------------------------3• Real-time target extraction-----------------------------------5• Target pre-processing-----------------------------------------6

Pre-processing--------------------------------------------------6 “Star” skeletonization-------------------------------------------7 Advantages of “star” skeletonization---------------------------8

• Human motion analysis---------------------------------------10 Significant features of the “star” skeleton----------------------10 Cycle detection--------------------------------------------------12

• Analysis------------------------------------------------------------13• Conclusion--------------------------------------------------------15

Introduction

• detecting and analyzing human motion in real time from video imagery has only recently become viable with algorithms like PJinder [9] and W4 [4].

• But !!! Two main drawbacks :

Introduction

• They are completely human specific

• They require a great deal of image-based information in order to work effectively

Real-time target extraction

• Temporal differencing

• Background subtraction

• Optical flow

Target pre-processing

• Pre-processing :

Target pre-processing

• “Star” skeletonization

Target pre-processing

• Advantages of “star” skeletonization : It is not iterative and computationally cheap. It explicitly provides a mechanism for controlling scale

sensitivity. It relies on no a priori human model.

Target pre-processing

Human motion analysis

• Significant features of the “star” skeleton

Human motion analysis

• Significant features of the “star” skeleton

Human motion analysis• Cycle detection

Analysis

• Figure 8. Histogram of cyclic motion frequency peaks. (a) The bias in often produces a frequency peak which is significantly higher than the peak produced by cyclic motion. (b) The pre-emphasis filter effectively removes this noise.

Analysis

Conclusion

• Further, two analysis techniques have been investigated which can broadly classify human motion. Body inclination can be measured from the “star” skeleton to determine the posture of the human, which derives clues as to the type of motion being executed.

• In addition, cyclic analysis of extremal points provides a very clean way of broadly distinguishing human motion in terms of walking and running and potentially even different types of gait.

Thanks for everybody’s listening

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