Automatic Extraction of Polar Adjectives for the Creation of Polarity Lexicons

Automatic creation of polarity lexicons is a crucial issue to be solved in order to reduce time andefforts in the first steps of Sentiment Analysis. In this paper we present a methodology based onlinguistic cues that allows us to automatically discover, extract and label subjective adjectivesthat should be collected in a domain-based polarity lexicon. For this purpose, we designed abootstrapping algorithm that, from a small set of seed polar adjectives, is capable to iterativelyidentify, extract and annotate positive and negative adjectives. Additionally, the methodautomatically creates lists of highly subjective elements that change their prior polarity evenwithin the same domain. The algorithm proposed reached a precision of 97.5% for positiveadjectives and 71.4% for negative ones in the semantic orientation identification task.

A Camera-Projector System for Robot Positioning by Visual Servoing

Positioning a robot with respect to objects by using data provided by a camera is a well known technique called visual servoing. In order to perform a task, the object must exhibit visual features which can be extracted from different points of view. Then, visual servoing is object-dependent as it depends on the object appearance. Therefore, performing the positioning task is not possible in presence of nontextured objets or objets for which extracting visual features is too complex or too costly. This paper proposes a solution to tackle this limitation inherent to the current visual servoing techniques. Our proposal is based on the coded structured light approach as a reliable and fast way to solve the correspondence problem. In this case, a coded light pattern is projected providing robust visual features independently of the object appearance

An approach to visual servoing based on coded light

Positioning a robot with respect to objects by using data provided by a camera is a well known technique called visual servoing. In order to perform a task, the object must exhibit visual features which can be extracted from different points of view. Then, visual servoing is object-dependent as it depends on the object appearance. Therefore, performing the positioning task is not possible in presence of non-textured objects or objects for which extracting visual features is too complex or too costly. This paper proposes a solution to tackle this limitation inherent to the current visual servoing techniques. Our proposal is based on the coded structured light approach as a reliable and fast way to solve the correspondence problem. In this case, a coded light pattern is projected providing robust visual features independently of the object appearance

Fear assessment in pigs exposed to a novel object test

The experiment aimed to study approach and locomotive behaviour as indicators of fear in a novel object test carried out in pigs. Thirty post-weaning (30 kg) and 30 finishing (90 kg) pigs were exposed to visual, auditory and olfactory novel stimuli during 2 different experiments. The facilities consisted of a test pen in which a trough was located. The trough contained chopped apples. Once the animals were trained to enter the test pen individually they were subjected to 3 different fear stimuli. These stimuli were applied in the test pen and next to the trough. The variables studied were feeding behaviour, approach behaviour (the distance and position of the animal with respect to the trough) and locomotive behaviour (general activity, reluctance to move, turning back and retreat attempts). Two groups were studied: saline and midazolam treated group. Twenty minutes before the start of the sessions, 15 post-weaning and finishing pigs received an intramuscular injection of 0.20 and 0.15 mg/kg, respectively, midazolam (Dormicum1). The saline pigs (15 animals per group) were injected with saline. The administration of midazolam increased the feeding behaviour and approaching behaviour, and reduced the locomotive behaviour. In front of the visual and olfactory stimuli post-weaning pigs showed a higher general activity than finishing pigs, but the contrary was found when the auditory stimulus was applied. The olfactory stimulus was more related to the turning back behaviour, whereas the visual stimulus was more related to retreat attempts. Although it could be concluded that reluctant to move was the most common response to the different fear stimuli applied in our study regardless of the age of animals, the combination of reluctant to move and turning back would be a good criterion to assess fear in domestic pigs. The use of midazolam as anxiolytic for studies of fear in commercial conditions in pigs is recommended.

Robust decoupled visual servoing based on structured light

This paper focuses on the problem of realizing a plane-to-plane virtual link between a camera attached to the end-effector of a robot and a planar object. In order to do the system independent to the object surface appearance, a structured light emitter is linked to the camera so that 4 laser pointers are projected onto the object. In a previous paper we showed that such a system has good performance and nice characteristics like partial decoupling near the desired state and robustness against misalignment of the emitter and the camera (J. Pages et al., 2004). However, no analytical results concerning the global asymptotic stability of the system were obtained due to the high complexity of the visual features utilized. In this work we present a better set of visual features which improves the properties of the features in (J. Pages et al., 2004) and for which it is possible to prove the global asymptotic stability

Plane-to-plane positioning from image-based visual servoing and structured light

In this paper we face the problem of positioning a camera attached to the end-effector of a robotic manipulator so that it gets parallel to a planar object. Such problem has been treated for a long time in visual servoing. Our approach is based on linking to the camera several laser pointers so that its configuration is aimed to produce a suitable set of visual features. The aim of using structured light is not only for easing the image processing and to allow low-textured objects to be treated, but also for producing a control scheme with nice properties like decoupling, stability, well conditioning and good camera trajectory

Visual management of sags and incidents gathered in distribution substations for power quality management

Monitor a distribution network implies working with a huge amount of data coining from the different elements that interact in the network. This paper presents a visualization tool that simplifies the task of searching the database for useful information applicable to fault management or preventive maintenance of the network

Intelligent task-level grasp mapping for robot control

In the future, robots will enter our everyday lives to help us with various tasks.For a complete integration and cooperation with humans, these robots needto be able to acquire new skills. Sensor capabilities for navigation in real humanenvironments and intelligent interaction with humans are some of the keychallenges.Learning by demonstration systems focus on the problem of human robotinteraction, and let the human teach the robot by demonstrating the task usinghis own hands. In this thesis, we present a solution to a subproblem within thelearning by demonstration field, namely human-robot grasp mapping. Robotgrasping of objects in a home or office environment is challenging problem.Programming by demonstration systems, can give important skills for aidingthe robot in the grasping task.The thesis presents two techniques for human-robot grasp mapping, directrobot imitation from human demonstrator and intelligent grasp imitation. Inintelligent grasp mapping, the robot takes the size and shape of the object intoconsideration, while for direct mapping, only the pose of the human hand isavailable.These are evaluated in a simulated environment on several robot platforms.The results show that knowing the object shape and size for a grasping taskimproves the robot precision and performance

Object and Scene Classification: what does a Supervised Approach Provide us?

Given a set of images of scenes containing different object categories (e.g. grass, roads) our objective is to discover these objects in each image, and to use this object occurrences to perform a scene classification (e.g. beach scene, mountain scene). We achieve this by using a supervised learning algorithm able to learn with few images to facilitate the user task. We use a probabilistic model to recognise the objects and further we classify the scene based on their object occurrences. Experimental results are shown and evaluated to prove the validity of our proposal. Object recognition performance is compared to the approaches of He et al. (2004) and Marti et al. (2001) using their own datasets. Furthermore an unsupervised method is implemented in order to evaluate the advantages and disadvantages of our supervised classification approach versus an unsupervised one

Chroma binary similarity and local alignment applied to cover song identification

We present a new technique for audio signal comparison based on tonal subsequence alignment and its application to detect cover versions (i.e., different performances of the same underlying musical piece). Cover song identification is a task whose popularity has increased in the Music Information Retrieval (MIR) community along in the past, as it provides a direct and objective way to evaluate music similarity algorithms.This article first presents a series of experiments carried outwith two state-of-the-art methods for cover song identification.We have studied several components of these (such as chroma resolution and similarity, transposition, beat tracking or Dynamic Time Warping constraints), in order to discover which characteristics would be desirable for a competitive cover song identifier. After analyzing many cross-validated results, the importance of these characteristics is discussed, and the best-performing ones are finally applied to the newly proposed method. Multipleevaluations of this one confirm a large increase in identificationaccuracy when comparing it with alternative state-of-the-artapproaches.

A two-stage approach for tonic identification in indian art music

In this paper we propose a new approach for tonic identification in Indian art music and present a proposal for acomplete iterative system for the same. Our method splits the task of tonic pitch identification into two stages. In the first stage, which is applicable to both vocal and instrumental music, we perform a multi-pitch analysis of the audio signal to identify the tonic pitch-class. Multi-pitch analysisallows us to take advantage of the drone sound, which constantlyreinforces the tonic. In the second stage we estimate the octave in which the tonic of the singer lies and is thusneeded only for the vocal performances. We analyse the predominant melody sung by the lead performer in order to establish the tonic octave. Both stages are individually evaluated on a sizable music collection and are shown toobtain a good accuracy. We also discuss the types of errors made by the method.Further, we present a proposal for a system that aims to incrementally utilize all the available data, both audio and metadata in order to identify the tonic pitch. It produces a tonic estimate and a confidence value, and is iterative in nature. At each iteration, more data is fed into the systemuntil the confidence value for the identified tonic is above a defined threshold. Rather than obtain high overall accuracy for our complete database, ultimately our goal is to develop a system which obtains very high accuracy on a subset of the database with maximum confidence.

Accessing forgotten memory traces from long-term memory via visual movements

Because memory retrieval often requires overt responses, it is difficult to determine to what extend forgetting occurs as a problem in explicit accessing of long-term memory traces. In this study, we used eye-tracking measures in combination with a behavioural task that favoured high forgetting rates to investigate the existence of memory traces from long-term memory in spite of failure in accessing them consciously. In 2 experiments, participants were encouraged to encode a large set of sound-picture56 location associations. In a later test, sounds were presented and participants were instructed to visually scan, before a verbal memory report, for the correct location of the associated pictures in an empty screen. We found the reactivation of associated memories by sound cues at test biased oculomotor behaviour towards locations congruent with memory representations, even when participants failed to consciously provide a memory report of it. These findings reveal the emergence of a memory-guided behaviour that can be used to map internal representations of forgotten memories from long-term memory.

Semantic domain and grammatical class effects in the picture-word interference paradigm

The role of grammatical class in lexical access and representation is still not well understood. Grammatical effects obtained in picture-word interference experiments have been argued to show the operation of grammatical constraints during lexicalization when syntactic integration is required by the task. Alternative views hold that the ostensibly grammatical effects actually derive from the coincidence of semantic and grammatical differences between lexical candidates. We present three picture-word interference experiments conducted in Spanish. In the first two, the semantic relatedness (related or unrelated) and the grammatical class (nouns or verbs) of the target and the distracter were manipulated in an infinitive form action naming task in order to disentangle their contributions to verb lexical access. In the third experiment, a possible confound between grammatical class and semantic domain (objects or actions) was eliminated by using action-nouns as distracters. A condition in which participants were asked to name the action pictures using an inflected form of the verb was also included to explore whether the need of syntactic integration modulated the appearance of grammatical effects. Whereas action-words (nouns or verbs), but not object-nouns, produced longer reaction times irrespective of their grammatical class in the infinitive condition, only verbs slowed latencies in the inflected form condition. Our results suggest that speech production relies on the exclusion of candidate responses that do not fulfil task-pertinent criteria like membership in the appropriate semantic domain or grammatical class. Taken together, these findings are explained by a response-exclusion account of speech output. This and alternative hypotheses are discussed.

Using appearance and context for outdoor scene object classification

We propose a probabilistic object classifier for outdoor scene analysis as a first step in solving the problem of scene context generation. The method begins with a top-down control, which uses the previously learned models (appearance and absolute location) to obtain an initial pixel-level classification. This information provides us the core of objects, which is used to acquire a more accurate object model. Therefore, their growing by specific active regions allows us to obtain an accurate recognition of known regions. Next, a stage of general segmentation provides the segmentation of unknown regions by a bottom-strategy. Finally, the last stage tries to perform a region fusion of known and unknown segmented objects. The result is both a segmentation of the image and a recognition of each segment as a given object class or as an unknown segmented object. Furthermore, experimental results are shown and evaluated to prove the validity of our proposal