Neural Attention-Driven Non-Maximum Suppression for Person Detection.

Non-maximum suppression (NMS) is a post-processing step in almost every visual object detector. NMS aims to prune the number of overlapping detected candidate regions-of-interest (RoIs) on an image, in order to assign a single and spatially accurate detection to each object. The default NMS algorithm (GreedyNMS) is fairly simple and suffers from severe drawbacks, due to its need for manual tuning.

Public opinion monitoring through collective semantic analysis of tweets.

The high popularity of Twitter renders it an excellent tool for political research, while opinion mining through semantic analysis of individual tweets has proven valuable. However, exploiting relevant scientific advances for collective analysis of Twitter messages in order to quantify general public opinion has not been explored. This paper presents such a novel, automated public opinion monitoring mechanism, consisting of a semantic descriptor that relies on Natural Language Processing algorithms.

Multimodal Stereoscopic Movie Summarization Conforming to Narrative Characteristics.

Video summarization is a timely and rapidly developing research field with broad commercial interest, due to the increasing availability of massive video data. Relevant algorithms face the challenge of needing to achieve a careful balance between summary compactness, enjoyability, and content coverage. The specific case of stereoscopic 3D theatrical films has become more important over the past years, but not received corresponding research attention.

Stereoscopic medical data video quality issues.

Stereoscopic medical videos are recorded, e.g., in stereo endoscopy or during video recording medical/dental operations.