100 research outputs found
Analyzing Tracklets for the Detection of Abnormal Crowd Behavior
No full textCrowd behavior analysis is still an open problem in computer vision which has recently attracted more interest from vision communities. One of the main challenges is to detect abnormalities in densely crowded environments both in the space and in time domains. This implies to isolate the frames where abnormalities occur (we refer to it as frame level) and to localize within these frames, the area that generated the abnormalities (we refer to it as pixel level). The major challenge in abnormality detection is that there is no clear definition of abnormalities as they are basically context dependent and can be defined as outliers of normal distributions. With this widely accepted definition, the existing approaches for detecting abnormalities in crowd are mainly classified into three categories: i) object-based method, ii) holistic approach, and iii) hybrid methods. Figure 1. A) Shibuya crossing (japan). b) mecca (saudi arabia). c) tracklets extracted from UCSD dataset
Depth Perception Within Peripersonal Space Using Head-Mounted Display
No full textNaceri A, Chellali R. Depth Perception Within Peripersonal Space Using Head-Mounted Display. Presence: Teleoperators and Virtual Environments. 2011;20(3):254-272
Depth Perception within Virtual Environments: A Comparative Study Between Wide Screen Stereoscopic Displays and Head Mounted Devices
No full textNaceri A, Chellali R, Dionnet F, Toma S. Depth Perception within Virtual Environments: A Comparative Study Between Wide Screen Stereoscopic Displays and Head Mounted Devices. In: 2009 Computation World: Future Computing, Service Computation, Cognitive, Adaptive, Content, Patterns. IEEE; 2009: 460-466
Do Observers Perceive Depth in Reaching Task Within Virtual Environments?
No full textNaceri A, Hoinville T, Chellali R, Ortiz J, Hennig S. Do Observers Perceive Depth in Reaching Task Within Virtual Environments? In: ASME 2011 World Conference on Innovative Virtual Reality. ASMEDC; 2011: 309-314
Depth Perception Within Virtual Environments: Comparison Between two Display Technologies
No full textNaceri A, Chellali R, Dionnet F, Toma S. Depth Perception Within Virtual Environments: Comparison Between two Display Technologies. International Journal On Advances in Intelligent Systems. 2010;3:51-64
Social Robots and Wearable Sensors for Mitigating Meltdowns in Autism - A Pilot Test
No full textYoung individuals with ASD may exhibit challenging behaviors. Among these, self-injurious behavior (SIB) is the most devastating for a person’s physical health and inclusion within the community. SIB refers to a class of behaviors that an individual inflicts upon himself or herself, which may potentially result in physical injury (e.g. hitting one’s own head with the hand or the wrist, banging one’s head on the wall, biting oneself and pulling out one’s own hair). We evaluate the feasibility of a wrist-wearable sensor in detecting challenging behaviors in a child with autism prior to any visible signs through the monitoring of the child’s heart rate, electrodermal activity, and movements. Furthermore, we evaluate the feasibility of such sensor to be used on an ankle instead of the wrist to reduce harm due to hitting oneself by hands and to improve wearable tolerance. Thus, we conducted two pilot tests. The first test involved a wearable sensor on the wrist of a child with autism. In a second test, we investigated wearable sensors on the wrist and on the ankle of a neurotypical child. Both pilot test results showed that the readings from the wearable sensors correlated with the children’s behaviors that were obtained from the videos taken during the tests. Wearable sensors could provide additional information that can be passed to social robots or to the caregivers for mitigating SIBs
Depth Discrimination of Constant Angular Size Stimuli in Action Space: Role of Accommodation and Convergence Cues
No full textIn our daily life experience, the angular size of an object correlates with its distance from the observer, provided that the physical size of the object remains constant. In this work, we investigated depth perception in action space (i.e., beyond the arm reach), while keeping the angular size of the target object constant. This was achieved by increasing the physical size of the target object as its distance to the observer increased. To the best of our knowledge, this is the first time that a similar protocol has been tested in action space, for distances to the observer ranging from 1.4 to 2.4m. We replicated the task in virtual and real environments and we found that the performance was significantly different between the two environments. In the real environment, all participants perceived the depth of the target object precisely. Whereas, in virtual reality the responses were significantly less precise, although, still above chance level in 16 of the 20 observers. The difference in the discriminability of the stimuli was likely due to different contributions of the convergence and the accommodation cues in the two environments. The values of Weber fractions estimated in our study were compared to those reported in previous studies in peripersonal and action space
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