La concurrence imparfaite Monopole, oligopole, et concurrence monopolistique.
Mining Actor Correlations with Hierarchical Concurrence Pasring
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Transcript of Mining Actor Correlations with Hierarchical Concurrence Pasring
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Mining Actor Correlations with Hierarchical Concurrence Pasring
Reporters: R98922004 Yun-Nung Chen, R98922033 Yu-Cheng Liu
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Reference
Ming Actor Correlations with Hierarchical Concurrence Parsing (ICASSP 2010) Kun Yuan, Hongxun Yao, Rongrong Ji,
Xiaoshuai Sun Computer Science & Technology, Harbin
Institute of Technology
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Outline
Introduction Actor Indexing Mining Actor Correlations
Context-Based Actor Concurrence Graph Ranking Concurrent Shots Actor Correlation Changes Analysis
Experimental Results
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Introduction
Actor correlations graph interfaces
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Introduction
Actor correlations graph interfaces
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Introduction
Actor correlations graph interfaces Top 20 shots
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Overview
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Actor Indexing
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Locating Actors
Shot boundary detection (SBD) Shots and scenes
Locating actor faces & face tracking algorithm Face set: different poses from the same
actor
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Clustering Actors
2D-PCA reduces dimension Features of same person may
distribute discretely in feature space Given 2 face sets Fk and Fl, 2 pose sets
If distance < T, 2 face sets belong to the same person
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Clustering Actors
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Mining Actor Correlations
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Context-Based Actor Concurrence A shot and its surrounding shots may
present a plot between two actors in video Gaussian weight measurement
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Context-Based Actor Concurrence
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Hierarchical Concurrence
Scene level correlation
Video level correlation
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Hierarchical Concurrence
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All Actor correlations graph
Construct correlations graph from
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Ranking Concurrent Shots
A single character i
Character correlations between i and j
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Ranking Concurrent Shots
Given i, j, sort RankScore<i, j>(k) for all k Show top 20 shots
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Actor Correlation Changes Analysis Two actors’ correlation changes with
story Analyze the difference of concurrence
R(i, j)A
correlation measure between i and j in the part A
Change ratio Hlp
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Experimental Results
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Experiment Setup
20 hours video of “Friends” TV series About 4000 shots Over 800 face sets
Clustering into about 60 face sets (T = 0.25)
Manual labeling to 17 actors
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Evaluation
The actor concurrence precision in all ranking shots is up to 90%
The precision of each two actor’s co-occurrence in ranking top 20 is up to 98%
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Thanks for your attention.