This paper describes the LIG participation to the MediaEval 2011 Affect Task on violent scenes ’ detection in Hollywood movies. We submitted only the required run (shot classi-fication run) with a minimal system using only the visual information. Color, texture and SIFT descriptors were ex-tracted from extracted key frames. The performance was below the one of systems using both audio and visual infor-mation but it appeared quite good in precision
Detecting violent scenes in videos is an important content understanding functionality, e.g., for pr...
Detecting violent scenes in videos is an important content understanding functionality, e.g., for pr...
International audienceIn this paper, we report on the creation of a publicly available, common evalu...
This paper describes the LIG participation to the MediaEval 2011 Affect Task on violent scenes ’ det...
Affect Task: Violent Scenes Detection Task (working notes paper) - Proceedings at http://ceur-ws.org...
Affect Task: Violent Scenes Detection Task (working notes paper) - Proceedings at http://ceur-ws.org...
This paper provides a description of the MediaEval 2011 Affect Task: Violent Scenes Detection. This ...
International audienceThis paper provides a description of the MediaEval 2012 Affect Task: Violent S...
International audienceThis paper provides a description of the MediaEval 2013 Affect Task Violent Sc...
International audienceThe MediaEval 2012 A ect Task is the continuation of the MediaEval 2011 A ect ...
The MediaEval 2015 Affective Impact of Movies Task chal-lenged participants to automatically find vi...
We present a comprehensive evaluation of performance of visual feature representations for MediaEval...
This paper describes the participation of the TUB-IRML group to the MediaEval 2014 Violent Scenes De...
International audienceThis paper presents the work done at Technicolor and INRIA regarding the Media...
Without doubt general video and sound, as found in large multimedia archives, carry emotional inform...
Detecting violent scenes in videos is an important content understanding functionality, e.g., for pr...
Detecting violent scenes in videos is an important content understanding functionality, e.g., for pr...
International audienceIn this paper, we report on the creation of a publicly available, common evalu...
This paper describes the LIG participation to the MediaEval 2011 Affect Task on violent scenes ’ det...
Affect Task: Violent Scenes Detection Task (working notes paper) - Proceedings at http://ceur-ws.org...
Affect Task: Violent Scenes Detection Task (working notes paper) - Proceedings at http://ceur-ws.org...
This paper provides a description of the MediaEval 2011 Affect Task: Violent Scenes Detection. This ...
International audienceThis paper provides a description of the MediaEval 2012 Affect Task: Violent S...
International audienceThis paper provides a description of the MediaEval 2013 Affect Task Violent Sc...
International audienceThe MediaEval 2012 A ect Task is the continuation of the MediaEval 2011 A ect ...
The MediaEval 2015 Affective Impact of Movies Task chal-lenged participants to automatically find vi...
We present a comprehensive evaluation of performance of visual feature representations for MediaEval...
This paper describes the participation of the TUB-IRML group to the MediaEval 2014 Violent Scenes De...
International audienceThis paper presents the work done at Technicolor and INRIA regarding the Media...
Without doubt general video and sound, as found in large multimedia archives, carry emotional inform...
Detecting violent scenes in videos is an important content understanding functionality, e.g., for pr...
Detecting violent scenes in videos is an important content understanding functionality, e.g., for pr...
International audienceIn this paper, we report on the creation of a publicly available, common evalu...