Nonverbal Communication through Facial Expression in Diverse Conditions

In this chapter, we investigated computer vision technique for facial expression recognition, which increase both - the recognition rate and computational efficiency. Local and global appearance-based features are combined in order to incorporate precise local texture and global shapes. We proposed Multi-Level Haar (MLH) feature based system, which is simple and fast in computation. The driving factors behind using the Haar were its two interesting properties - signal compression and energy preservation. To depict the importance of facial geometry, we first segmented the facial components like eyebrows, eye, and mouth, and then applied feature extraction on these facial components only. Experiments are conducted on three well known publicly available expression datasets CK, JAFFE, TFEID and in-house WESFED dataset. The performance is measured against various template matching and machine learning classifiers. We achieved highest recognition rate for proposed operator with Discriminant Analysis Classifier. We studied the performance of proposed approach in several scenarios like expression recognition from low resolution, recognition from small training sample space, recognition in the presence of noise and so forth.

Use and Perceptions of Pedestrian Navigation Apps: Findings from Bologna and Porto

Pedestrian Navigation Applications (PNAs) provide assistance in terms of self-localization, space recognition, and turn-by-turn navigation. The use, motivations and perceptions associated with these applications have been under investigated due to users being insufficiently involved in their design and development. This paper analyses the extent to which PNAs are used for assisting people to walk, the frequencies and reasons of using these applications, the perceptions about them, and the barriers preventing them from being used. The study is supported by a questionnaire (N = 1438) that was administered in Bologna (Italy) and Porto (Portugal). Results indicated that 42% of the respondents use PNAs mainly on an occasional basis to find locations and the shortest routes. Google Maps was the preferred navigation service. Statistical tests showed that PNAs were more likely to be used by younger adults and students. The lack of need was the main reason for not using these apps, due to the good spatial knowledge of the cities or the non-use of the pedestrian mode for regular trips. Respondents would like to have apps that are more accurate, usable, and adjusted to pedestrian navigation. The findings described in this paper could be helpful for future designs of PNAs, especially to match pedestrian needs more effectively and to enhance the role of these apps in promoting healthier and sustainable lifestyles.

The influence of leisure-based community activities on neighbourhood support and the social cohesion of communities in Spain

To analyse the effects of leisure-based community activities in improving neighbourhood support and social cohesion, data were collected in two neighbourhoods of Barcelona (Spain) through questionnaires and interviews. The results indicate that promoting neighbourhood support requires a different strategy from promoting participation in leisure-based activities aimed at developing social cohesion within a community. The study also suggests various useful strategies to strengthen the effects of leisure-based community activities. The strategies recommended revolve around networking, use of the public space, recognition of diversity and conflict management.

The entanglement of knowing and being: Hegel, ontology and education in the 21st century

There has been a revived interest Georg Wilhelm Friedrich Hegel. Notions emanating from his philosophy concerning the human person and that human beings together create and sustain phenomena through social practice speaks of a relational ontology that has relevance for contemporary education. This article argues that such ontology needs to be considered alongside the epistemological concerns of education. From Hegel’s writing, five interdependent ideas are delineated which have relevance for a relational ontology appropriate for contemporary education ‐ consciousness, self-consciousness, social space, recognition and identity. From these, three propositions for a social ontology of education ‐ learning as a socially constructed activity, learning as the formation of identity and learning as recognition ‐ are posited and discussed.

Multi-Sensor Information Ensemble-Based Automatic Parking System for Vehicle Parallel/Nonparallel Initial State

The goal of automatic parking system is to accomplish the vehicle parking to the specified space automatically. It mainly includes parking space recognition, parking space matching, and trajectory generation. It has been developed enormously, but it is still a challenging work due to parking space recognition error and trajectory generation for vehicle nonparallel initial state with parking space. In this study, the authors propose multi-sensor information ensemble for parking space recognition and adaptive trajectory generation method, which is also robust to vehicle nonparallel initial state. Both simulation and real vehicle experiments are conducted to prove that the proposed method can improve the automatic parking system performance.

Parking Space Recognition Method Based on Parking Space Feature Construction in the Scene of Autonomous Valet Parking

At present, the realization of autonomous valet parking (AVP) technology does not achieve information interaction between the parking spaces and vehicles, and accurate parking spaces information perception cannot be obtained when the accuracy of the search is not precise. In addition, when using the camera vision to identify the parking spaces, traditional parking space features such as parking lines and parking angles recognition are susceptible to light and environment. Especially when the vehicle nearby partially occupies the parking space to be parked, it is not easy to determine whether it is a valid empty parking space. This paper proposes a parking space recognition method based on parking space features in the scene of AVP. By constructing the multi-dimensional features containing the parking space information, the cameras are used to extract features’ contour, locate features’ position and recognize features. In this paper, a new similarity calculation formula is proposed to recognize the stained features through template matching algorithm. According to the relative position relationship between the feature and parking space, the identification of effective empty parking spaces and their boundaries is realized. The experimental results show that compared with the recognition of traditional parking lines and parking angles, this method can identify effective empty parking spaces even when the light conditions are complex and the parking spaces are partially occupied by adjacent vehicles, which simplifies the recognition algorithm and improves the reliability of the parking spaces identification.

Research on the Method of Urban Jobs-Housing Space Recognition Combining Trajectory and POI Data

With the gradual emergence of the separation and dislocation of urban jobs-housing space, rational planning of urban jobs-housing space has become the core issue of national land-spatial planning. To study the existing relationship between workspaces and living spaces, a new method to identify jobs-housing space is proposed, which not only considers the static spatial distribution of urban public facilities but also identifies the jobs-housing space by analyzing the real mobility characteristics of people from a humanistic perspective. This method provides a new framework for the identification of urban jobs-housing space by integrating point-of-interest (POI) and trajectory data. The method involves three steps: Firstly, based on the trajectory data, we analyze the characteristics of the dynamic flow of passengers in the grid and construct the living factors and working factors to identify the distribution of jobs-housing space. Secondly, we reclassify the POIs to calculate the category ratios of different types of POIs in the grid to identify the jobs-housing space. Finally, an OR operation is performed on the results obtained by the two methods to obtain the final recognition result. We selected Haikou City as the experimental area to verify the method proposed in this paper. The experimental results show that the recognition accuracy of the travel flow model is 72.43%, the POI quantitative recognition method’s accuracy is 74.94%, and the accuracy of the method proposed in this paper is 85.90%, which is significantly higher than the accuracy of the previous two methods. Therefore, the method proposed here can serve as a reference for subsequent research on urban jobs-housing space.