PAMOCAT: Automatic retrieval of specified postures
In order to understand and model the non-verbal communicative conduct of humans, it seems fruitful to combine qualitative methods (Conversation Analysis) and quantitative techniques (motion capturing). A Tools for data visualization and annotation is important as they constitute a central interface between different research approaches and methodologies. We have developed the pre-annotation tool PAMOCAT that detects motion segments of individual joints. A sophisticated user interface easily allows the annotating person to find correlations between different joints and to export combined qualitative and quantitative annotations to standard annotation tools. Using this technique we are able to examine complex setups with three persons in tight conversion. A functionality to search for special postures of interest and display the frames in an overview makes it easy to analyze difference phenomenas in Conversation Analysis.
Code (0)
등록된 구현이 없습니다.
Tasks
Data VisualizationMotion SegmentationRetrievalTime Series AnalysisSimilar Papers 제목 키워드 기반
A Novel Approach to Managing Lower Face Complexity in Signing Avatars
An avatar that produces legible, easy-to-understand signing is one of the essential components to an effective automatic signed/spoken translation system. Facial nonmanual signals are essential to natural signing, but un…
TranslationUnsupervised Video Understanding by Reconciliation of Posture Similarities
Understanding human activity and being able to explain it in detail surpasses mere action classification by far in both complexity and value. The challenge is thus to describe an activity on the basis of its most fundame…
Action ClassificationRetrievalSuper-ResolutionVideo UnderstandingLeveraging Query Resolution and Reading Comprehension for Conversational Passage Retrieval
This paper describes the participation of UvA.ILPS group at the TREC CAsT 2020 track. Our passage retrieval pipeline consists of (i) an initial retrieval module that uses BM25, and (ii) a re-ranking module that combines …
Passage RetrievalReading ComprehensionRe-RankingRetrievalApplying Incremental Deep Neural Networks-based Posture Recognition Model for Injury Risk Assessment in Construction
Monitoring awkward postures is a proactive prevention for Musculoskeletal Disorders (MSDs)in construction. Machine Learning (ML) models have shown promising results for posture recognition from Wearable Sensors. However,…
Incremental LearningJNLP Team: Deep Learning for Legal Processing in COLIEE 2020
We propose deep learning based methods for automatic systems of legal retrieval and legal question-answering in COLIEE 2020. These systems are all characterized by being pre-trained on large amounts of data before being …
Deep LearningInformation RetrievalQuestion AnsweringRetrieval