Continuous Action Recognition Based on Sequence Alignment

Continuous action recognition is more challenging than isolated recognition because classification and segmentation must be simultaneously carried out. We build on the well known dynamic time warping (DTW) framework and devise a novel visual alignment technique, namely dynamic frame warping (DFW), which performs isolated recognition based on per-frame representation of videos, and on aligning a test sequence with a model sequence. Moreover, we propose two extensions which enable to perform recognition concomitant with segmentation, namely one-pass DFW and two-pass DFW. These two methods have their roots in the domain of continuous recognition of speech and, to the best of our knowledge, their extension to continuous visual action recognition has been overlooked. We test and illustrate the proposed techniques with a recently released dataset (RAVEL) and with two public-domain datasets widely used in action recognition (Hollywood-1 and Hollywood-2). We also compare the performances of the proposed isolated and continuous recognition algorithms with several recently published methods

THE ASPECTS OF SEMIOTICS USING BARTHES’S THEORY ON A SERIES OF UNFORTUNATE EVENTS MOVIE POSTER

Penelitian ini membahas tentang makna denotative dan konotative yang terdapat pada poster film A Series of Unfortunate Events. Makna denotasi dan konotasi merupakan bagian dari aspek semiotik dalam menganalisa gambar. Analisa mengenai makna denotasi dan konotasi ini berdasarkan pada teori Barthes.Teori Barthes merupakan perkembangan ilmu semiotik dalam analisa objek gambar. Dalam teori ini, peran pembaca menjadi hal yang terpenting untuk dikaji. Peran pembaca inilah yang akan memunculkan berbagai persepsi mengenai makna dari sebuah gambar. Makna ini dapat dilihat dari dua segi yaitu denotasi dan konotasi. Makna Denotasi adalah makna dasar yang ada pada gambar tanpa mengaitkannya dengan nilai sosial budaya yang ada di dalamnya.Makna ini merupakan makna yang ada pada pada level pertama dari sistem semiotik. Sedangkan makna konotasi adalah makna subjektif yang muncul ketika kita mengaitkannya dengan unsur emosi dan perasaan pembacanya dengan nilai budaya yang mereka miliki. Makna konotasi ini merupakan level kedua dari sistem semiotik. Untuk mendapatkan makna konotasi sebuah mitos juga dapat dipakai dalam menganalisa sebuah gambar. Mitos inilah yang digunakan untuk menganalisa unsur budaya dan ideologi dalam gambar. Dalam analisa makna denotasi dan konotasi yang ada pada gambar ini, Barthes membaginya ke dalam dua bagian yaitu tanda verbal dan tanda non verbal agar tidak terjadi kesalahpahaman dalam mengamatiny

Stylistic Creativity in the Utilization of Management Tools

We analyze the role of management instruments in the development of collective activity and in the dynamics of organization, recurring to pragmatic and semiotic theories. In dualist representation-based theories (rationalism, cognitivism), instruments are seen as symbolic reflections of situations, which enable actors to translate their complex concrete activities into computable models. In interpretation-based theories (pragmatism, theory of activity, situated cognition), instruments are viewed as signs interpreted by actors to make sense of their collective activity, in an ongoing and situated manner. Instruments combine objective artefacts and interpretive schemes of utilization. They constrain interpretation and utilization, but do not completely determine them: they define genus (generic classes) of collective activity, but they leave space for individual or local interpretive schemes and stylistic creation in using them. A major part of organizational dynamics takes place in the permanent interplay between instrumental genus and styles. Whereas representation-based theories can be acceptable approximations in stable and reasonably simple organizational settings, interpretation-based theories make uncertain and complex situations more intelligible. They view emotions and creativity as a key part of the interpretive process, rather than as external biases of a rational modelling process. For future research, we wish to study how interpretation-based theories should impact managerial practices and improve, not only intelligibility, but also actionability of instruments and situations.Collective Activity; Genus; Instruments; Interpretation; Management Instruments; Performance Management; Pragmatism; Semiotics; Style

Neural Speed Reading with Structural-Jump-LSTM

Recurrent neural networks (RNNs) can model natural language by sequentially 'reading' input tokens and outputting a distributed representation of each token. Due to the sequential nature of RNNs, inference time is linearly dependent on the input length, and all inputs are read regardless of their importance. Efforts to speed up this inference, known as 'neural speed reading', either ignore or skim over part of the input. We present Structural-Jump-LSTM: the first neural speed reading model to both skip and jump text during inference. The model consists of a standard LSTM and two agents: one capable of skipping single words when reading, and one capable of exploiting punctuation structure (sub-sentence separators (,:), sentence end symbols (.!?), or end of text markers) to jump ahead after reading a word. A comprehensive experimental evaluation of our model against all five state-of-the-art neural reading models shows that Structural-Jump-LSTM achieves the best overall floating point operations (FLOP) reduction (hence is faster), while keeping the same accuracy or even improving it compared to a vanilla LSTM that reads the whole text.Comment: 10 page

Learning to Speak and Act in a Fantasy Text Adventure Game

We introduce a large scale crowdsourced text adventure game as a research platform for studying grounded dialogue. In it, agents can perceive, emote, and act whilst conducting dialogue with other agents. Models and humans can both act as characters within the game. We describe the results of training state-of-the-art generative and retrieval models in this setting. We show that in addition to using past dialogue, these models are able to effectively use the state of the underlying world to condition their predictions. In particular, we show that grounding on the details of the local environment, including location descriptions, and the objects (and their affordances) and characters (and their previous actions) present within it allows better predictions of agent behavior and dialogue. We analyze the ingredients necessary for successful grounding in this setting, and how each of these factors relate to agents that can talk and act successfully

Multisensory legal machines and legal act production

This paper expands on the concept of legal machine which was presented first at IRIS 2011 in Salzburg. The research subjects are (1) the creation of institutional facts by machines, and (2) multimodal communication of legal content to humans. Simple examples are traffic lights and vending machines. Complicated examples are computer-based information systems in organisations, form proceedings workflows, and machines which replace officials in organisations. The actions performed by machines have legal importance and draw legal consequences. Machines similarly as humans can be imposed status-functions of legal actors. The analogy of machines with humans is in the focus of this paper. Legal content can be communicated by machines and can be perceived by all of our senses. The content can be expressed in multimodal languages: textual, visual, acoustic, gestures, aircraft manoeuvres, etc. The concept of encapsulatation of human into machine is proposed. Herein humanintended actions are communicated through the machine’s output channel. Encapsulations can be compared with deities and mythical creatures that can send gods’ messages to people through the human mouth. This paper also aims to identify law production patterns by machines