Latest News

Course @ CEMA Srishti School of Design, Bangalore, IN

  • #862
  • 10/11/11

From November 21st to the 2nd of December, I’ll have the pleasure to lead a course and workshop with Prayas Abhinav at the Center for Experimental Media Arts in the Srishti School of Design in Banaglore, IN.  Many thanks to Meena Vari for all her help in organizing the project.

Stories are flowing trees

Key words:  3D, interactive projects, data, histories, urban, creative coding, technology, sculpture, projection mapping

Project Brief:

Urban realities are more like fictions, constructed through folklore, media and policy. Compressing these constructions across time would offer some possibilities for the emergence of complexity and new discourse. Using video projections adapted for 3D surfaces, urban histories will become data and information – supple, malleable, and material.

The project will begin with a one week workshop by Parag Mital on “Creative Coding” using the openFrameworks platform for C/C++ coding”.

About the Artists:

Prayas Abhinav

Presently he teaches at the Srishti School of Art, Design and Technology and is a researcher at the Center for Experimental Media Arts (CEMA). He has taught in the past at Dutch Art Institute (DAI) and Center for Environmental Planning and Technology (CEPT).
He has been supported by fellowships by Openspace India (2009), TED (2009), Center for Media Studies (CMS) (2006), Public Service Broadcasting Trust (PSBT) (2006), Sarai/CSDS (2005). He has presented his projects and proposals in the last few years at Periferry, Guwahati (2010), Exit Art, New York (2010), Futuresonic, Manchester (2009), Wintercamp, Amsterdam (2009), 48c: Public Art Ecology (2008), Khoj (2008), Urban Climate Camp, ISEA (2008), Sensory Urbanism, Glasgow (2008), First Monday, Chicago (2006), The Paris Accord (2006) and PSBT/Prasar Bharti (2006).
He has also participated in the exhibitions Myth ?? Reality (2011) at The Guild, Mumbai, Continuum Transfunctioner (2010) at exhibit 320 in Delhi, Contested Space – Incursions (2010) at Gallery Seven Arts in Delhi and Astonishment of Being (2009) at the Birla Academy of Art and Culture in Kolkatta (2009).

http://prayas.in

Parag K Mital (London)

Parag K Mital is an American-born London-based PhD-student in Arts and Computational Technology at Goldsmiths, University of London working on augmented realities and audiovisual resynthesis. As an audiovisual installation artist, his work encourages the audience to directly question the processes surrounding perception through introspection and curiosity from experiencing real-time models of audiovisual perception. His work has traveled extensively in London, Athens, and Moscow, including the London Science Museum and the British Film Institute. As an educator he has taught at Edinburgh University, Goldsmiths, University of London, and is due to deliver a course on Audiovisual Processing for iPhone/iPad at the Victoria & Albert Museum in London.

http://pkmital.com

Workshop in “Creative Coding” using the openFrameworks platform

The workshop will cover the basics of openFrameworks, a c/c++ creative coding platform. This course will also introduce students to digital signal processing techniques in synthesis and analysis of audio and visual signals for interactive techniques using custom made libraries developed at Goldsmiths, University of London. Depending on interest, participants will also receive tutorial on developing for the iPhone/iPad in order to create real-time audiovisual apps.

http://www.openframeworks.cc
http://pkmital.com/home/code/
http://maximilian.strangeloop.co.uk/

Memory Mosaicing

  • #855
  • 03/11/11

A product of my PhD research is now available on the iPhone App Store (for a small cost!): View in App Store.

This application is motivated by my interests in experiencing an Augmented Perception and of course very much inspired by some of the work here at Goldsmiths. The application of existing approaches in soundspotting/mosaicing to a real-time stream and situated in the real-world allows one to play with their own sonic memories, and certainly requires an open ear for new experiences. Succinctly, the app records segments of sounds in real-time using it’s own listening model, as you walk around in different environment (or sit at your desk). These segments are constantly built up the longer the app is left running to form a database (working memory model) for which to understand new sounds. Incoming sounds are then matched to this database and the closest matching sound is played instead. What you get is a polyphony of sound memories triggered by the incoming feed of audio, and an app which sounds more like your environment the longer it is left to run. A sort of gimmicky feature of this app is the ability to learn a song from your iTunes Library. What this lets you do is experience your sonic world as your favorite hip-hop song or whatever you listen to.

Hope you have a chance to try it out and please forward to anyone of interest.

Concatenative Video Synthesis (or Video Mosaicing)

  • #830
  • 08/10/11

prototype

Working closely with my adviser Mick Grierson, I have developed a way to resynthesize existing videos using material from another set of videos. This process starts by learning a database of objects that appear in the set of videos to synthesize from. The target video to resynthesize is then broken into objects in a similar manner, but also matched to objects in the database. What you get is a resynthesis of the video that appears as beautiful disorder. Here are two examples, the first using Family Guy to resynthesize The Simpsons. And the second using Jan Svankmajer’s Food to resynthesize Jan Svankmajer’s Dimensions of Dialogue.

Google Earth + Atlantis Space Shuttle

  • #640
  • 10/07/11

I managed to catch the live feed from NASA.gov of the Atlantis Space Shuttle launch yesterday. Though what I found really interesting was a real-time virtual reality of the space shuttle launch from inside Google Earth. Screen-capture with obligatory 12x speedup to retain attention span below:

Lunch Bites @ CULTURE Lab, Newcastle University

  • #638
  • 10/07/11

I was recently invited to the CULTURE lab at Newcastle University by director, Atau Tanaka. I would say it has the resources and creative power of 5 departments all housed in one spacious building. In the 12-some studios housed over 3 floors, over the course of 2 short days, I found people building multitouch tables, controlling synthesizers with the touch of fabric, and researching augmented spatial sonic realities. There is a full suite of workshop tools including a laser cutter, multiple multi-channel sound studios, full stage/theater with stage lighting and multiple projection, radio lab, and tons of light and interesting places to sit and do whatever you feel like doing. The other thing I found really interesting is there are no “offices”. Instead, the staff are dispersed amongst the students in the twelve-some studios, picking a new desk perhaps whenever they need a change of scenery? If you are ever in the area, it is certainly worth a visit, and I’m sure the people there will be very open to tell you what they are up to.

I also had the pleasure to give a talk on my PhD research in Resynthesizing Audiovisual Perception with Augmented Reality at the Lunch BITES seminar series. Slides are below, though the embedded media is removed. Comments are welcome!

Download (PDF, 1.12MB)

Creative Community Spaces in INDIA

  • #621
  • 22/06/11

Jaaga – Creative Common Ground
Bangalore
http://www.jaaga.in/

CEMA – Center for Experimental Media Arts at Srishti School of Art, Design and Technology
Bangalore
http://cema.srishti.ac.in/site/

Bar1 – non-profit exchange programme by artists for artists to foster the local, Indian and international mutual exchange of ideas and experiences through guest residencies in Bangalore
Bangalore
http://www.bar1.org

Sarai – a space for research, practice, and conservation about the contemporary media and urban constellations.
New Dehli
http://www.sarai.net/

Khoj/International Artists’ Association – artist led, alternative forum for experimentation and international exchange
New Dehli
http://www.khojworkshop.org/

Periferry – To create a nomadic space for hybrid art practices. It is a laboratory for people cross- disciplinary practices. The project focuses on the creation of a network space for negotiating the challenge of contemporary cultural production. It is located on a ferry barge on river Brahmaputra and is docked in Guwhati, Assam.
Narikolbari, Guwahati
http://www.periferry.in/

Point of View – non-profit organization that brings the points of view of women into community, social, cultural and public domains through media, art and culture.
Bombay
http://www.pointofview.org/

Majilis – a center for rights discourse and inter-disciplinary arts initiatives
Bombay
http://majlisbombay.org/

Camp – not an “artists collective” but a space, in which ideas and energies gather, and become interests and forms.
Bombay
http://www.camputer.org/

ChitraKarKhana – A fully independent, small scale unit for experimental media.
Bombay
http://chitrakarkhana.net/

Facial Appearance Modeling/Tracking

  • #602
  • 26/05/11


I’ve been working on developing a method for automatic head-pose tracking, and along the way have come to model facial appearances. I start by initializing a facial bounding box using the Viola-Jones detector, a well known and robust detector used for training objects. This allows me to centralize the face. Once I know where the 2D plane of the face is in an image, I can register an Active Shape Model like so:

After multiple views of the possible appearance variations of my face, including slight rotations, I construct an appearance model.

The idea I am working with is using the first components of variations of this appearance model for determining pose. Here I show the first two basis vectors and the images they reconstruct:

As you may notice, these two basis vectors very neatly encode rotation. By looking at the eigenvalues of the model, you can also interpret pose.

Short Time Fourier Transform using the Accelerate framework

  • #591
  • 14/04/11

Using the libraries pkmFFT and pkm::Mat, you can very easily perform a highly optimized short time fourier transform (STFT) with direct access to a floating-point based object.

Get the code on my github:
http://github.com/pkmital/pkmFFT
Depends also on: http://github.com/pkmital/pkmMatrix

/*
 *  pkmSTFT.h
 *
 *  STFT implementation making use of Apple's Accelerate Framework (pkmFFT)
 *
 *  Created by Parag K. Mital - http://pkmital.com
 *  Contact: parag@pkmital.com
 *
 *  Copyright 2011 Parag K. Mital. All rights reserved.
 *
 *	Permission is hereby granted, free of charge, to any person
 *	obtaining a copy of this software and associated documentation
 *	files (the "Software"), to deal in the Software without
 *	restriction, including without limitation the rights to use,
 *	copy, modify, merge, publish, distribute, sublicense, and/or sell
 *	copies of the Software, and to permit persons to whom the
 *	Software is furnished to do so, subject to the following
 *	conditions:
 *
 *	The above copyright notice and this permission notice shall be
 *	included in all copies or substantial portions of the Software.
 *
 *	THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
 *	EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
 *	OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
 *	NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
 *	HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
 *	WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
 *	FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
 *	OTHER DEALINGS IN THE SOFTWARE.
 *
 *
 *  Usage:
 *
 *  // be sure to either use malloc or __attribute__ ((aligned (16))
 *  size_t buffer_size = 4096;
 *  float *sample_data = (float *) malloc (sizeof(float) * buffer_size);
 *  pkm::Mat magnitude_matrix, phase_matrix;
 *
 *  pkmSTFT *stft;
 *  stft = new pkmSTFT(512);
 *  stft.STFT(sample_data, buffer_size, magnitude_matrix, phase_matrix);
 *  fft.ISTFT(sample_data, buffer_size, magnitude_matrix, phase_matrix);
 *  delete stft;
 *
 */

#include "pkmFFT.h"
#include "pkmMatrix.h"

class pkmSTFT
{
public:

	pkmSTFT(size_t size)
	{
		fftSize = size;
		numFFTs = 0;
		fftBins = fftSize/2;
		hopSize = fftSize/4;
		windowSize = fftSize;
		bufferSize = 0;

		initializeFFTParameters(fftSize, windowSize, hopSize);
	}

	void initializeFFTParameters(size_t _fftSize, size_t _windowSize, size_t _hopSize)
	{
		fftSize = _fftSize;
		hopSize = _hopSize;
		windowSize = _windowSize;

		// fft constructor
		FFT = new pkmFFT(fftSize);
	}

	void STFT(float *buf, size_t bufSize, pkm::Mat &M_magnitudes, pkm::Mat &M_phases)
	{
		// pad input buffer
		int padding = ceilf((float)bufSize/(float)fftSize) * fftSize - bufSize;
		float *padBuf;
		if (padding) {
			printf("Padding %d sample buffer with %d samples\n", bufSize, padding);
			padBufferSize = bufSize + padding;
			padBuf = (float *)malloc(sizeof(float)*padBufferSize);
			// set padding to 0
			memset(&(padBuf[bufSize]), 0, sizeof(float)*padding);
			// copy original buffer into padded one
			memcpy(padBuf, buf, sizeof(float)*bufSize);	}
		else {
			padBuf = buf;
			padBufferSize = bufSize;
		}

		// create output fft matrix
		numWindows = (padBufferSize - fftSize)/hopSize + 1;

		if (M_magnitudes.rows != numWindows && M_magnitudes.cols != fftBins) {
			printf("Allocating %d bins x %d windows matrix for STFT\n", fftBins, numWindows);
			M_magnitudes.reset(numWindows, fftBins, true);
			M_phases.reset(numWindows, fftBins, true);
		}

		// stft
		for (size_t i = 0; i < numWindows; i++) {

			// get current col of freq mat
			float *magnitudes = M_magnitudes.row(i);
			float *phases = M_phases.row(i);
			float *buffer = padBuf + i*hopSize;

			FFT->forward(0, buffer, magnitudes, phases);	

		}
		// release padded buffer
		if (padding) {
			free(padBuf);
		}
	}

	void ISTFT(float *buf, size_t bufSize, pkm::Mat &M_magnitudes, pkm::Mat &M_phases)
	{
		int padding = ceilf((float)bufSize/(float)fftSize) * fftSize - bufSize;
		float *padBuf;
		if (padding)
		{
			printf("Padding %d sample buffer with %d samples\n", bufSize, padding);
			padBufferSize = bufSize + padding;
			padBuf = (float *)calloc(padBufferSize, sizeof(float));
		}
		else {
			padBuf = buf;
			padBufferSize = bufSize;
		}

		pkm::Mat M_istft(padBufferSize, 1, padBuf, false);

		for(size_t i = 0; i < numWindows; i++)
		{
			float *buffer = padBuf + i*hopSize;
			float *magnitudes = M_magnitudes.row(i);
			float *phases = M_phases.row(i);

			FFT->inverse(0, buffer, magnitudes, phases);
		}

		memcpy(buf, padBuf, sizeof(float)*bufSize);
		// release padded buffer
		if (padding) {
			free(padBuf);
		}
	}

private:

	pkmFFT				*FFT;

	size_t				sampleRate,
						numFFTs,
						fftSize,
						fftBins,
						hopSize,
						bufferSize,
						padBufferSize,
						windowSize,
						numWindows;
};

Real FFT/IFFT with the Accelerate Framework

  • #576
  • 14/04/11

Apple’s Accelerate Framework can really speed up your code without thinking too much. And it will also run on an iPhone. Even still, I did bang my head a few times trying to get a straightforward Real FFT and IFFT working, even after consulting the Accelerate documentation (reference and source code), stackoverflow (here and here), and an existing implementation (thanks to Chris Kiefer and Mick Grierson). Still, the previously mentioned examples weren’t very clear as they did not handle the case of overlapping FFTs which I was doing in the case of a STFT or they did not recover the power spectrum, or they just didn’t work for me (lots of blaring noise).

Get the code on my github:
http://github.com/pkmital/pkmFFT

/*
 *  pkmFFT.h
 *
 *  Real FFT wraper for Apple's Accelerate Framework
 *
 *  Created by Parag K. Mital - http://pkmital.com
 *  Contact: parag@pkmital.com
 *
 *  Copyright 2011 Parag K. Mital. All rights reserved.
 *
 *	Permission is hereby granted, free of charge, to any person
 *	obtaining a copy of this software and associated documentation
 *	files (the "Software"), to deal in the Software without
 *	restriction, including without limitation the rights to use,
 *	copy, modify, merge, publish, distribute, sublicense, and/or sell
 *	copies of the Software, and to permit persons to whom the
 *	Software is furnished to do so, subject to the following
 *	conditions:
 *
 *	The above copyright notice and this permission notice shall be
 *	included in all copies or substantial portions of the Software.
 *
 *	THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
 *	EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
 *	OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
 *	NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
 *	HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
 *	WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
 *	FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
 *	OTHER DEALINGS IN THE SOFTWARE.
 *
 *  Additional resources:
 *      http://developer.apple.com/library/ios/#documentation/Accelerate/Reference/vDSPRef/Reference/reference.html
 *      http://developer.apple.com/library/ios/#documentation/Performance/Conceptual/vDSP_Programming_Guide/SampleCode/SampleCode.html
 *      http://stackoverflow.com/questions/3398753/using-the-apple-fft-and-accelerate-framework
 *      http://stackoverflow.com/questions/1964955/audio-file-fft-in-an-os-x-environment
 *
 *
 *  This code is a very simple interface for Accelerate's fft/ifft code.
 *  It was built out of hacking Maximilian (Mick Grierson and Chris Kiefer) and
 *  the above mentioned resources for performing a windowed FFT which could
 *  be used underneath of an STFT implementation
 *
 *  Usage:
 *
 *  // be sure to either use malloc or __attribute__ ((aligned (16))
 *  float *sample_data = (float *) malloc (sizeof(float) * 4096);
 *  float *allocated_magnitude_buffer =  (float *) malloc (sizeof(float) * 2048);
 *  float *allocated_phase_buffer =  (float *) malloc (sizeof(float) * 2048);
 *
 *  pkmFFT *fft;
 *  fft = new pkmFFT(4096);
 *  fft.forward(0, sample_data, allocated_magnitude_buffer, allocated_phase_buffer);
 *  fft.inverse(0, sample_data, allocated_magnitude_buffer, allocated_phase_buffer);
 *  delete fft;
 *
 */

#include <Accelerate/Accelerate.h>

class pkmFFT
{
public:

	pkmFFT(int size = 4096, int window_size = 4096)
	{
		fftSize = size;					// sample size
		fftSizeOver2 = fftSize/2;
		log2n = log2f(fftSize);			// bins
		log2nOver2 = log2n/2;

		in_real = (float *) malloc(fftSize * sizeof(float));
		out_real = (float *) malloc(fftSize * sizeof(float));
		split_data.realp = (float *) malloc(fftSizeOver2 * sizeof(float));
		split_data.imagp = (float *) malloc(fftSizeOver2 * sizeof(float));

		windowSize = window_size;
		window = (float *) malloc(sizeof(float) * windowSize);
		memset(window, 0, sizeof(float) * windowSize);
		vDSP_hann_window(window, window_size, vDSP_HANN_DENORM);

		scale = 1.0f/(float)(4.0f*fftSize);

		// allocate the fft object once
		fftSetup = vDSP_create_fftsetup(log2n, FFT_RADIX2);
		if (fftSetup == NULL) {
			printf("\nFFT_Setup failed to allocate enough memory.\n");
		}
	}
	~pkmFFT()
	{
		free(in_real);
		free(out_real);
		free(split_data.realp);
		free(split_data.imagp);

		vDSP_destroy_fftsetup(fftSetup);
	}

	void forward(int start,
				 float *buffer,
				 float *magnitude,
				 float *phase)
	{
		//multiply by window
		vDSP_vmul(buffer, 1, window, 1, in_real, 1, fftSize);

		//convert to split complex format with evens in real and odds in imag
		vDSP_ctoz((COMPLEX *) in_real, 2, &split_data, 1, fftSizeOver2);

		//calc fft
		vDSP_fft_zrip(fftSetup, &split_data, 1, log2n, FFT_FORWARD);

		split_data.imagp[0] = 0.0;

		for (i = 0; i < fftSizeOver2; i++)
		{
			//compute power
			float power = split_data.realp[i]*split_data.realp[i] +
							split_data.imagp[i]*split_data.imagp[i];

			//compute magnitude and phase
			magnitude[i] = sqrtf(power);
			phase[i] = atan2f(split_data.imagp[i], split_data.realp[i]);
		}
	}

	void inverse(int start,
				 float *buffer,
				 float *magnitude,
				 float *phase,
				 bool dowindow = true)
	{
		float *real_p = split_data.realp, *imag_p = split_data.imagp;
		for (i = 0; i < fftSizeOver2; i++) {
			*real_p++ = magnitude[i] * cosf(phase[i]);
			*imag_p++ = magnitude[i] * sinf(phase[i]);
		}

		vDSP_fft_zrip(fftSetup, &split_data, 1, log2n, FFT_INVERSE);
		vDSP_ztoc(&split_data, 1, (COMPLEX*) out_real, 2, fftSizeOver2);

		vDSP_vsmul(out_real, 1, &scale, out_real, 1, fftSize);

		// multiply by window w/ overlap-add
		if (dowindow) {
			float *p = buffer + start;
			for (i = 0; i < fftSize; i++) {
				*p++ += out_real[i] * window[i];
			}
		}
	}

private:

	size_t				fftSize,
						fftSizeOver2,
						log2n,
						log2nOver2,
						windowSize,
						i;					

	float				*in_real,
						*out_real,
						*window;

	float				scale;

    FFTSetup			fftSetup;
    COMPLEX_SPLIT		split_data;

};

Augmented Sonic Reality

  • #551
  • 21/03/11

I recently gave two talks, one for the PhDs based in the Electronic Music Studios, and another for the PhDs in Arts and Computational Technology. I received some very valuable feedback, and having to incorporate what I’ve been working on in a somewhat presentable manner also had a lot of benefit. The talk abstract (which is very abstract) is posted below with a few references listed. Please feel free to comment and open a discussion, or post any references that may be of interest.

Abstract:
An augmented sonic reality aims to register digital sound content with an existing physical space. Perceptual mappings between an agent in such an environment and the augmented content should be both continuous and effective, meaning the intentions of an agent should be taken into consideration in any affective augmentations. How can an embedded intelligence such as an iPhone equipped with detailed sensor information such as microphone, accelerometer, gyrometer, and GPS readings infer the behaviors of its user in creating affective, realistic, and perceivable augmented sonic realities tied to their situated experiences? Further, what can this augmented domain reveal about our own ongoing sensory experience of our sonic environment?

Keywords: augmented, reality, sonic, enactive, perception, memory, behavior, sensors, gesture, embodied, situated, acoustic, ecology, liminality

References:
Augoyard and Torgue, “Sonic Experience”, McGill-Queen’s University Press, 2005.
Arfib, D. “Organised Sound”, 2002.
E. Corteel, “Synthesis of directional sources using Wave Field Synthesis, possibilities and limitations.” EURASIP Journal on Advances in Signal Processing, special issue on Spatial Sound and Virtual Acoustics, January, 2007
Lemaitre, G., Houix, O., Visell, Y., Franinovic, K., Misdariis, N., Susini, P. “Toward the Design and Evaluation of Continuous Sound in Tangible Interfaces: The Spinotron”, International Journal of Human Computer Studies, no 67, 2009
K. Nguyen, C. Suied, I. Viaud-Delmon, O. Warusfel, “Spatial audition in a static virtual environment : the role of auditory-visual interaction.” Journal of Virtual Reality and Broadcasting, 2009
M. Noisternig, B. Katz, S. Siltanen, L. Savioja, “Framework for Real-Time Auralization in Architectural Acoustics.” Acta acustica united with Acustica, vol. 94, no 6, November, 2008
R. Murray Schafer, “The Soundscape”, Destiny Books, 1977.
J. Tardieu, P. Susini, F. Poisson, P. Lazareff, S. McAdams, “Perceptual study of soundscapes in train stations.” Applied Acoustics, vol. 69, no 12, December, 2008
Strategies of mapping between gesture data and synthesis model parameters using perceptual spaces. D. Arfib, J. M. Couturier, L. Kessous, V. Verfaille. Organised Sound, International Journal of Music Technology, Volume 7, Issue 2 , pages 127-144, 2002.
D. Arfib, J-M. Couturier, L. Kessous , “Expressiveness and digital musical instrument design”, in Journal of New Music Research,Vol. 34, No. 1, pages 125 – 136, 2005.
N. d’Alessandro, O. Babacan, B. Bozkurt, T. Dubuisson, A. Holzapfel, L. Kessous, A. Moinet, M. V. Lieghe, “RAMCESS 2.X framework – expressive voice analysis for realtime and accurate synthesis of singing”, Journal On Multimodal User Interfaces, Springer Berlin/Heidelberg, Vol. 2, Nr. 2, September, pages 133-144, 2008.
L. Kessous, G. Castellano, G. Caridakis, Multimodal emotion recognition in speech-based interaction using facial expression, body gesture and acoustic analysis, Journal on Multimodal User Interfaces, Vol. 3, Issue 1, Springer Berlin/Heidelberg, December 12, pages 33-48, 2009.
G.Caridakis, K. Karpouzis, M. Wallace, L. Kessous, N.Amir, Multimodal user’s affective state analysis in naturalistic interaction, Journal on Multimodal User Interfaces, Vol. 3, Issue 1, Springer Berlin/Heidelberg, December 15, pages 49-66, 2009.
Anton Batliner, Stefan Steidl, Bjoern Schuller, Dino Seppi, Turid Vogt, Johannes Wagner, Laurence Devillers, Laurence Vidrascu, Noam Amir, Loic Kessous and Vered Aharonson. Whodunnit – Searching for the Most Important Feature Types Signalling Emotion-Related User States in Speech. Computer Speech and Language, volume 25, No. 1, pages 4–28, 2011.

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