Assessing similarity models for human‐motion retrieval applications

The development of motion capturing devices poses new challenges in the exploitation of human‐motion data for various application fields, such as computer animation, visual surveillance, sports, or physical medicine. Recently, a number of approaches dealing with motion data have been proposed, suggesting characteristic motion features to be extracted and compared on the basis of similarity. Unfortunately, almost each approach defines its own set of motion features and comparison methods; thus, it is hard to fairly decide which similarity model is the most suitable for a given kind of human‐motion retrieval application. To cope with this problem, we propose the human motion model evaluator, which is a generic framework for assessing candidate similarity models with respect to the purpose of the target application. The application purpose is specified by a user in form of a representative sample of categorized motion data. Respecting such categorization, the similarity models are assessed from the effectiveness and efficiency points of view using a set of space‐complexity, information‐retrieval, and performance measures. The usability of the framework is demonstrated by case studies of three practical examples of retrieval applications focusing on recognition of actions, detection of similar events, and identification of subjects. Copyright © 2015 John Wiley & Sons, Ltd.     

D-Index: Distance Searching Index for Metric Data Sets

In order to speedup retrieval in large collections of data, index structures partition the data into subsets so that query requests can be evaluated without examining the entire collection. As the complexity of modern data types grows, metric spaces have become a popular paradigm for similarity retrieval. We propose a new index structure, called D-Index, that combines a novel clustering technique and the pivot-based distance searching strategy to speed up execution of similarity range and nearest neighbor queries for large files with objects stored in disk memories. We have qualitatively analyzed D-Index and verified its properties on actual implementation. We have also compared D-Index with other index structures and demonstrated its superiority on several real-life data sets. Contrary to tree organizations, the D-Index structure is suitable for dynamic environments with a high rate of delete/insert operations.     

Approximate similarity retrieval with M-trees

Motivated by the urgent need to improve the efficiency of similarity queries, approximate similarity retrieval is investigated in the environment of a metric tree index called the M-tree. Three different approximation techniques are proposed, which show how to forsake query precision for improved performance. Measures are defined that can quantify the improvements in performance efficiency and the quality of approximations. The proposed approximation techniques are then tested on various synthetic and real-life files. The evidence obtained from the experiments confirms our hypothesis that a high-quality approximated similarity search can be performed at a much lower cost than that needed to obtain the exact results. The proposed approximation techniques are scalable and appear to be independent of the metric used. Extensions of these techniques to the environments of other similarity search indexes are also discussed. Received July 7, 1998 / Accepted October 13, 1998     

Effective and efficient similarity searching in motion capture data

Multimedia Tools and Applications - Motion capture data describe human movements in the form of spatio-temporal trajectories of skeleton joints. Intelligent management of such complex data is a...     

The effect of vitamin E on cortisol and lactate levels and on the acid-base equilibrium in calves exposed to transportation stress

The objective of this study was to examine the effect of vitamin E administration on plasma levels of cortisol and lactate, and on acid base balance in transported calves. In the study, eight calves, aged approx. ten days, divided into two groups, were used. 20 mg of tocopherol-acetate per kg body weight were administered orally to each of the four experimental calves 24 hours before loading. The calves were transported by road for 3 hours. Blood samples collected before and after the transportation were examined for acid base balance, lactate, and plasma vitamin E and cortisol levels. The administration of vitamin E led to a decrease of cortisol levels in 24 hours (from 7.6 +/- 9.5 to 4.2 +/- 0.2 nmol/l) as well as to a significant increase (p < 0.05) of plasma vitamin E levels 26 h after administration (from 2.52 +/- 1.36 to 12.28 +/- 6.14 mumol/l). There was no difference between the groups in cortisol response due to transportation stress (Tab. III). The transportation caused typical stress changes in lactate levels and acid base balance (lactacidaemia and the tendency to acidosis, Tab. III, IV). There was approx. threefold increase in plasma lactate concentrations due to transportation (from 2.49 +/- 0.69 to 6.35 +/- 3.75 mmol/l). The results of the present study demonstrated metabolic changes which has been reported to be typical of mild physiological stress reaction. In the present study, vitamin E had no significant effect on plasma levels of cortisol, and lactate, and acid-base balance.     

LSTM-based real-time action detection and prediction in human motion streams

Multimedia Tools and Applications - Motion capture data digitally represent human movements by sequences of 3D skeleton configurations. Such spatio-temporal data, often recorded in the stream-based...     

ConceptRank for search-based image annotation

Multimedia Tools and Applications - Multimedia information is becoming an ubiquitous part of our lives, which brings an equally ubiquitous need for efficient multimedia retrieval. One of the...     

Principles of Holism for sequential twig pattern matching

Modern applications face the challenge of dealing with structured and semi-structured data. They have to deal with complex objects, most of them presenting some kind of internal structure, which often forms a hierarchy. Though XML documents are the most known, chemical compounds, CAD drawings, web-sites and many other applications have to deal with similar problems. In such environments, ordered and unordered tree pattern matching are the fundamental search operations. One of the main thrusts of research activities for tree pattern matching is the class of holistic approaches. Their ultimate goal is to evaluate a query twig as a whole by relying on sequential access patterns and non trivial auxiliary storage structures, typically stored in main memory. Based on the pre/post-order ranks of individual tree nodes, we establish strong theoretical bases as a foundation for correct and efficient holistic pattern matching algorithms. In particular, we define and prove sufficient and necessary conditions to minimize the amount of data retained in memory, thus introducing a correct and complete framework on which different holistic solutions can be compared. We also show how these rules can be applied for building algorithms for ordered and unordered tree-pattern matching. Thanks to the above theoretical achievements, each holistic algorithm gains in efficiency as it is directly implemented on the adopted numbering scheme, avoids expensive matching refinements and keeps memory requirements stable. An experimental analysis and comparison with previous approaches confirms the superiority of our approach tested on synthetic as well as real-life data sets.