A human perception model for multi-modal feedback in telepresence systems

Author(s):  
P. Kammermeier ◽  
M. Buss
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ilya A. Surov ◽  
E. Semenenko ◽  
A. V. Platonov ◽  
I. A. Bessmertny ◽  
F. Galofaro ◽  
...  

AbstractThe paper presents quantum model of subjective text perception based on binary cognitive distinctions corresponding to words of natural language. The result of perception is quantum cognitive state represented by vector in the qubit Hilbert space. Complex-valued structure of the quantum state space extends the standard vector-based approach to semantics, allowing to account for subjective dimension of human perception in which the result is constrained, but not fully predetermined by input information. In the case of two distinctions, the perception model generates a two-qubit state, entanglement of which quantifies semantic connection between the corresponding words. This two-distinction perception case is realized in the algorithm for detection and measurement of semantic connectivity between pairs of words. The algorithm is experimentally tested with positive results. The developed approach to cognitive modeling unifies neurophysiological, linguistic, and psychological descriptions in a mathematical and conceptual structure of quantum theory, extending horizons of machine intelligence.


Author(s):  
Juan Gutiérrez ◽  
Gabriel Gómez-Perez ◽  
Jesús Malo ◽  
Gustavo Camps-Valls

Support vector machine (SVM) image coding relies on the ability of SVMs for function approximation. The size and the profile of the e-insensitivity zone of the support vector regression (SVR) at some specific image representation determines (a) the amount of selected support vectors (the compression ratio), and (b) the nature of the introduced error (the compression distortion). However, the selection of an appropriate image representation is a key issue for a meaningful design of the e-insensitivity profile. For example, in image coding applications, taking human perception into account is of paramount relevance to obtain a good rate-distortion performance. However, depending on the accuracy of the considered perception model, certain image representations are not suitable for SVR training. In this chapter, we analyze the general procedure to take human vision models into account in SVR-based image coding. Specifically, we derive the condition for image representation selection and the associated e-insensitivity profiles.


2015 ◽  
Author(s):  
Nobuyasu Itoh ◽  
Gakuto Kurata ◽  
Ryuki Tachibana ◽  
Masafumi Nishimura

2021 ◽  
pp. 004051752199803
Author(s):  
Shuhei Watanabe ◽  
Takahiko Horiuchi

Nowadays, numerous products use artificial leather as it is a cost-effective alternative to genuine leather. However, products made from artificial leather may leave impressions on consumers that are dissimilar to those left by products made of genuine leather. In other words, products that use artificial leather but are perceived as genuine leather are more attractive to consumers. Therefore, in this study, we aimed to understand and quantify the factors that affect the mechanism via which consumers perceive a leather product to be made of genuine leather. We conducted several experiments to evaluate the hypothesis regarding human perception. Measurement experiments were performed to obtain the visual and physical properties of such impressions. We estimated the representative impressions formed by people during their interaction with leather samples through subjective experiments and derived models of these impressions in terms of the measured properties. Subjective evaluation experiments were performed under visual, tactile, and visual–tactile conditions. Finally, we quantified leather “authenticity” using these representative impressions. Participants, who are general consumers, were divided into two groups according to their familiarity with leather. The “authenticity” perception model of the group familiar with leather was constructed under visual and visual–tactile conditions, whereas the model of the group unfamiliar with leather was constructed under visual–tactile conditions, suggesting the influence of a cross-modal phenomenon. The results of this study can be applied to develop attractive artificial leather, which is expected to contribute to the protection of animal rights while promoting the sale of artificial leather products.


2017 ◽  
Vol 131 (1) ◽  
pp. 19-29 ◽  
Author(s):  
Marianne T. E. Heberlein ◽  
Dennis C. Turner ◽  
Marta B. Manser

2012 ◽  
Author(s):  
R. A. Grier ◽  
H. Thiruvengada ◽  
S. R. Ellis ◽  
P. Havig ◽  
K. S. Hale ◽  
...  

Author(s):  
Rajesh Kumar Gupta ◽  
L. N. Padhy ◽  
Sanjay Kumar Padhi

Traffic congestion on road networks is one of the most significant problems that is faced in almost all urban areas. Driving under traffic congestion compels frequent idling, acceleration, and braking, which increase energy consumption and wear and tear on vehicles. By efficiently maneuvering vehicles, traffic flow can be improved. An Adaptive Cruise Control (ACC) system in a car automatically detects its leading vehicle and adjusts the headway by using both the throttle and the brake. Conventional ACC systems are not suitable in congested traffic conditions due to their response delay.  For this purpose, development of smart technologies that contribute to improved traffic flow, throughput and safety is needed. In today’s traffic, to achieve the safe inter-vehicle distance, improve safety, avoid congestion and the limited human perception of traffic conditions and human reaction characteristics constrains should be analyzed. In addition, erroneous human driving conditions may generate shockwaves in addition which causes traffic flow instabilities. In this paper to achieve inter-vehicle distance and improved throughput, we consider Cooperative Adaptive Cruise Control (CACC) system. CACC is then implemented in Smart Driving System. For better Performance, wireless communication is used to exchange Information of individual vehicle. By introducing vehicle to vehicle (V2V) communication and vehicle to roadside infrastructure (V2R) communications, the vehicle gets information not only from its previous and following vehicle but also from the vehicles in front of the previous Vehicle and following vehicle. This enables a vehicle to follow its predecessor at a closer distance under tighter control.


Sign in / Sign up

Export Citation Format

Share Document