Norihiro Hagita

People re-identification across non-overlapping cameras using group features

People is grouped based on the spatio-temporal features of their trajectories.From people groups, new group features for people re-identification are extracted.The group features can be employed with any kind of existing appearance features.Experiments demonstrated that the group features improve people re-identification. Display Omitted This paper proposes methods for people re-identification across non-overlapping cameras. We improve the robustness of re-identification by using additional group features acquired from the groups of people detected by each camera. People are grouped by discriminatively classifying the spatio-temporal features of their trajectories into those of grouped people and non-grouped people. Thereafter, three group features are obtained in each group and utilized with other general features of each person (e.g., color histogram, transit time between cameras, etc.) for people re-identification. Our experimental results have demonstrated improvements in people grouping and people re-identification when our proposed methods have been applied to a public dataset.

Comfortable autonomous navigation based on collision prediction in blind occluded regions

This paper presents an approach for human passenger stress reduction while riding a personal mobility autonomous vehicle. The particular vehicle of interest is a robotic autonomous wheelchair which can provide mobility assistance in pedestrian paths. State of the art algorithms for autonomous vehicles mainly focus on collision free path planning and safe control for obstacle avoidance. This work studies comfort factors of the passenger while riding the vehicle. We propose a method for velocity control of the robotic wheelchair based on the concept of “behavior dependent observability” to reduce stress from the collision prediction in blind regions. Behavior dependent observability (BDO) is defined as the visible collision area against dynamic obstacles which is free from collision. By using BDO, the velocity of the robotic wheelchair is computed so that passengers feel comfortable. Experimental results based on physiological measurements (heart rate and galvanic skin response) show that the control of the robotic wheelchair using the behavior dependent observability decreases stressful situations for passengers.

Chat robot coupling machine responses and social media comments for continuous conversation

In this paper we propose a communicative robot that facilitates talk with a user who lacks a chance of verbal communication with others for any reasons (e.g. the elderly who live alone). As our first trial, this system is designed to support a user to talk while watching a TV program. It features two conversation techniques: realizing natural timing of simultaneous response and providing interesting utterances from social media networks related to the TV program the user is watching. To achieve natural response timing, the proposed system includes three response functions: backchannel, repetition and machine answering. While the system keeps talking using the three kinds of responses, it searches human text comments about the TV program from social network services (SNS). When a comment is found, the robot outputs the comment by synthetic speech. A preliminary experiment is conducted to evaluate how the proposed response technique encourages a user to speak to the chat robot. The results show that average number of user utterances with the proposed robot using social media networks and the above three functions is significantly higher than that when the chat robot only outputs social media comments.

A TV Chat Robot with Time-Shifting Function for Daily-Use Communication

This paper attempts to improve a chatting robot that enables to chat with a user while the user is watching television programs. Previously developed robot interacts with two problems because it utters chat sources from social media such as Twitter. Firstly, it is delayed with a few seconds between the contents of TV program and social media comments, so what robot’s utterance doesn’t relate to the scene being broadcast. Secondly, there is overlap between the utterance of TV and the robot. These problems often make users discomfort when they want to continue to daily-use communication. Therefore, this paper introduces the time-shifting method allowing to improve both problems simultaneously. The experiments for using subjective evaluation by 12 subjects and three kinds of TV program are conducted to compare the robot applied time-shifted and previous one. The results show that the robot with time shifting improves user satisfaction in terms of the synchronization of TV scenes and chat sources.

Social Common Sense Modeling of a Spread-out Queue in Public Space for a Service Robot

This paper describes method to model social common sense for an interactive robot that provides customers in a spread-out queue with a service in a public space. Interactive robots that provide services in a public space, such as handing out flyers or touting, have been developed. To provide such services, robot behavior must be appropriate, i.e., comparable to that of a human. Such appropriate behavior is based on social common sense, which is a human concept. However, modeling social common sense when a human provides a service in public space is difficult. This paper focuses on a service, e.g., handing out flyers, provided by a robot to customers waiting in a queue where the order of the queue is unclear. By modeling the unconscious order of the queue as social common sense, we develop a robot that can provide a service in an appropriate order. To model the unconscious order of the queue, the human order is defined by the geometric relationship between a human and a robot and the queue order that an individual recognizes. Through an experiment conducted in a public space, we confirm that the robot with the modeled common sense hands out flyers to customers in an appropriate order. In addition, the robot can give advice to a customer who cuts into the line.

An experimental study of the use of multiple humanoid robots as a social communication medium

This paper reports on an experimental investigation into the use of humanoid robots as a communication medium. Many social robots have been developed and tried for use in urban environments, but due to their limited perception, their degree of interactivity is still far poorer than that of humans. In this study, our approach used the robots as a non-interactive medium. We propose using robots as a passive-social medium, in which multiple robots converse with each other.

A surround view image generation method with low distortion for vehicle camera systems using a composite projection

This paper proposes a surround view image generation method for vehicle camera systems. To assist the driver during parking, a view with easy comprehension of distance and direction between the vehicle and objects is desirable. However, the conventional method of using an equidistant projection for generating a surround image of wide field of view causes image distortion, with straight lines appearing curved. This prevents the driver from correctly understanding the distance and direction of objects. Our proposed method uses a composite projection that combines two projection models: perspective projection and equidistant projection. This strategy can generate an image without distortion by using perspective projection near the vehicle and provides a wide field of view using equidistant projection. The experiments demonstrate the generation from parking scene images, using our proposed method, of a surround image with a wide field of view and no distortion near the vehicle.

Diminished reality for acceleration stimulus: Motion sickness reduction with vection for autonomous driving

This paper presents an approach for motion sickness reduction while riding an autonomous vehicle. It proposes the Diminished Reality (DR) method for an acceleration stimulus to reduce motion sickness for the autonomous vehicle. One of the main causes of motion sickness is a repeated acceleration. In order to diminish the acceleration stimulus in the autonomous vehicle, vection illusion is used to induce the user to make a preliminary movement against the real acceleration. The Balance Wii Board is used to measure participants movement of the center of gravity to verify the effectiveness of the method with vection. The experimental result of 9 participants shows that the proposed method of using vection could reduce acceleration stimulus compared with the conventional method.

Does a Reciprocated Hug from a Robot Encourage Self-Disclosure?

This paper presents the effects of being hugged by a robot for self-disclosure. In human-human interaction, physical interactions such as hug behaviors are essential ways for communication with close persons. We developed a teddy-bear-like robot that can give reciprocal hugs (i.e., firstly a person hugs the robot and then the robot hugs the person) to people and experimentally investigated its effects toward their self-disclosure behaviors. In our trial, a robot asked participants to give a hug, and then asked them to chat freely with and without a reciprocated hug. In the experiment, the participants interact with the robot at least ten minutes, and additional ten minutes if they want. The experiment results showed significant differences for the amount of self-disclosure among participants.

Lesioned-Part Identification by Classifying Entire-Body Gait Motions

This paper proposes a physical motion evaluation system based on human pose sequences estimated by a depth sensor. While most similar systems measure and evaluate the motion of only a part of interest e.g., knee, the proposed system comprehensively evaluates the motion of the entire body. The proposed system is designed for observing a human motion in daily life in order to find the sign of aging and physical disability. For daily use, in this paper, we focus on walking motions. Walking motions with a variety of physical disabilities are recorded and modeled for classification purpose. This classification is achieved with a set of pose features extracted from walking motion sequences. In experiments, the proposed features extracted from the entire body allowed us to identify where a subject was injured with 81.1i¾?% accuracy. The superiority of the entire-body features was also validated in estimating the degree of lesion in contrast to local features extracted from only a body part of interest 77.1i¾?% vs 65i¾?%.