Ashish Tawari

Email: ashish.tawari@gmail.com
Phone: +1 (858) 736-1901

Laboratory for Intelligent and Safe Automobiles (LISA)
Computer Vision and Robotics Research Laboratory (CVRR)
University of California, San Diego
La Jolla, CA 92037

 

 
About Me Publications Resume Projects CVRR

LISA

 
 

Short pdf version

Reference: Prof. Mohan M. Trivedi, Department of Electrical and Computer Engineering, University of California, San Diego.

Email: mtrivedi@ucsd.edu

Visa: F1

Interests:

Machine Vision, Machine Learning, Signal Processing, Sensor Fusion and Multi-Modal/Multi-Sensory Data Analytics.

Education:

  • Ph.D. Electrical and Computer Engineering, University of California, San Diego (UCSD), Expected Dec 2014.   

  • M.S.  Electrical and Computer Engineering, University of California, San Diego (UCSD), awarded, 2010.

  • B.S.   Electrical Engineering, Indian Institute of Technology, Bombay (IITB), India, awarded May 2006.

Skills and Tools:   

Programming Languages

C, C++, Python, Perl, Tcl

Software Packages

OpenCV, MATLAB, Qt, OpenGL, ADTF, HTK, Microsoft Visual Studio, Boost C++ Libraries

Software Development Tools

Makefile, Boost build system (bjam)

Hardware

Audio, Video, IP/Network Cameras, Microphone array, Familiar with Android-based devices (smart phones and Google-Glass)

Core competencies:

Computer vision, machine learning, signal processing, speech processing, multimodal fusion, audio-visual expression recognition, visual saliency modeling, Distributed and Synchronized Multimodal-Multisensory testbeds design (smart spaces and smart cars).

Learning/Inference:

Support Vector Machine, Adaboost, Random Forest, Clustering (k-means, spectral), Guassian Mixture Model, Hidden Markov Models, Probabilistic modeling, Regression techniques.

Select Courses:

UCSD: Random Processes(A+), Parameter Estimation I(A), Statistical Learning II(A), Speech Compression(A), Computer Vision and Multimodal System(A+), Computer Vision II(A+), Speech Recognition(A),  Numerical Optimization (A+), Introduction to Computer Graphics1 (S).  

IITB: Adaptive Signal Processing(AA), Wireless and Mobile Communication(AA), Communication Systems Theory(AA), Advanced Programming in C++(AA), Wavelets2(AU), Computer Organization, Architecture and Microprocessors(AB), Control Systems(AA), Signals and Systems(AA), Digital Circuits(AB), Computational Methods(AA).

(1satisfactory,  2 audited - Extra courses taken out of interest)

 

Professional Experience:  

 Software Engineer, Qualcomm India Pvt. Ltd.

Jul 06 - Jul 08

  • Analyzed the post-processing features like Equalizer/Filters, Re-sampler, Automatic Dynamic Range Control, Doppler Effect, audio visualization effects like Spectrum Analyzer.

  • Designed, developed and implemented dynamic priority based memory allocation (malloc) to enhance the concurrent playback of different decoders. The internal memory is a rare and useful resource and a bottle-neck for the concurrency requirement. Malloc not only uses the resource optimally but also prioritizes the decoders to facilitate the memory requirement for higher priority decoders.
    Awarded special recognition (
    QUALSTAR) for the contribution in the project.

  • Enhanced the data flow to meet low power requirement to increase the playback time (the period for which music can be played non-stop with the available power in phones). It improves the power utilization by factor of three.
    Awarded special recognition (
    QUALSTAR) for the contribution in the project.

Intern, QCT Multimedia RnD & Standard, Qualcomm Incorporated, San Diego, CA

 Jun 10 - Sept 10

  • Improved and Implemented high-quality low delay music coding scheme for next generation vocoders to handle music signal over voice channel at low bit rates (24/32 Kbps). Project involved coding of LPC residual in MDCT domain. Developed and implemented an innovative idea of identifying regions of interest and coding them in order of their perceptual importance.

    Awarded QUALSTAR for the exceptional contribution. Contribution was finally led to a patent publication.

Research/Teaching:
  • Reviewer, IEEE Intelligent Transportation Systems Conference (ITSC)

  • Reviewer, IEEE Intelligent Vehicle Symposium

Feb 12 - Present

Feb 12 - Present

UCSD Electrical and Computer Engineering Department, San Diego, CA

  • Graduate Student Researcher

Dec 10 - Present

Laboratory for Intelligent and Safe Automobiles (LISA): core group member involved in design, development and operation of powerful and novel real-world driving testbeds for research in intelligent vehicle systems.  Current research includes developing, data driven, machine-vision and machine-learning based methods to analyze driver behavior and intent along with surround situation criticality (object detection) for improving Active Safety Systems. Proposed a distributed camera framework to robustly and continuously monitor driver's state, which improved system's operational range over two-times. Developed a probabilistic model to infer driver's focus-of-attention. Deployed and demonstrated a real-time system, 'Attention-Guard', in Audi-A8 concept car (Audi sponsored project). The system is expected to enter pre-production stage for further testing and future commercial deployment (media and press releases: CBS, NPR, CNN (page 3)).

- Analyzed a big naturalistic driving data (>100 hours, collected over 2+ years) for novel research and algorithm development. 
- Designed and developed a time-synchronized multi-sensory data visualization interface (multiple videos, vehicle dynamics (time-series) data,  lidar/radar tracked objects, GPS map) to identify trends and relationships between different pieces of data.
- Developed 'Semiautomatic-Intelligent-Annotator', a platform for quick, simple and accurate data annotation - an essential step for supervised machine learning.
- Mentored junior graduate and undergraduate students.
-
Closely collaborated with industry sponsors (Electronic Research Laboratory and Audi, 2010-2013).

Technical aspect involves: SIFT, linear regression and circular-Hough transform (facial feature and iris detection/tracking); least square estimation (3D head pose calculation); saliency modeling using object detectors (car and pedestrian detection); Random Forest classifier and domain knowledge (human intent and focus-of-attention inference).

  • Graduate Student Researcher

Dec 08 - Dec 10

Computer Vision and Robotics Research Laboratory (CVRR): designed and developed distributed and synchronized multimodal, multisensory smart spaces and intelligent vehicles testbeds for understanding human/driver behavior. Analyzed and developed audiovisual methods to recognize emotional content of the video data. Completed an analysis to the most important audio cues to infer the emotion based on machine learning approach and extended the analysis to make it robust to background noise, e.g. in driving scenario. Furthermore, a novel facial expression recognition system, utilizing cross modal (audio cues) data association, is developed to  address the effect of speech generation on spontaneous facial expression, and demonstrated improved recognition rate. Relevant publications are listed below.

Audio analysis involves: silence, voiced/unvoiced region identification; pitch and energy contour calculation  (prosodic feature extraction); MFCC (spectral feature extraction); Support Vector Machine (SVM) classifier (emotion recognition);

Video analysis involves: image registration techniques (face alignment); Gabor wavelets and LBP (low level feature extraction); Adaboost and Correlation-based Feature Subset selection (feature selection); SVM classifier (facial expression recognition)

  • Statistical Learning(ECE 271B) class project: Facial expression recognition

Sept 09 - Nov 09

Developed and implemented an expression recognition system using face images. Project involved face detection, feature extraction (Gabor wavelets) and selection (using Adaboost), and classification module (SVMs) implementation. Further, relaxed frontal pose constraints on face images and used image registration technique as a front end to the system, and demonstrated improved recognition rate.
Instructor: Prof Nuno Vasconcelos.

  • Speech Recognition(ECE 252B) class project: Robust Automatic Speech Recognition System

Apr 09 - Jun 09

Designed and implemented a psycho-acoustical model of auditory perception as front-end to Hidden Markov Model (HMM) based ASR system. Addressed robustness of the model over conventional MFCC based ASR system under different noisy conditions.
Instructor: Prof Bhaskar Rao.

 IITB Electrical Engineering Department, India

  • B.Tech Project: Distributed computation over Arbitrary Sensor Network

Jul 05 - May 06

Formulated the optimization problem with minimum energy and time as constraint. Proved that the optimal solution falls in the category of NP-hard problem. Proposed a suboptimal solution for the problem.

Select Publications:

  • Ashish Tawari, Andreas Møgelmose, Sujitha Martin,  Thomas Moeslund and Mohan M. Trivedi, "First Person Attention Estimation by Simultaneous Analysis of Viewer and View," IEEE Intelligent Transportation Systems Conference, 2014. [oral presentation]

  • Ashish Tawari, Kuo Chen and Mohan M. Trivedi, "Where is the driver looking: Analysis of Head, Eye and Iris for Robust Gaze Zone Estimation," IEEE Intelligent Transportation Systems Conference, 2014. [oral presentation]

  • Eshed Ohn-Bar, Sujitha Martin, Ashish Tawari and Mohan Trivedi, "Title Towards Understanding Driver Activities from Head and Hand Coordinated Movements," IEEE international Conference on Pattern Recognition (ICPR), 2014. [Nominated for best industry related paper award]

  • Ashish Tawari and Mohan M. Trivedi, "Robust and Continuous Estimation of Driver Gaze Zone by Dynamic Analysis of Multiple Face Videos", IEEE Intelligent Vehicles Symposium, June 2014. [oral presentation]

  • Ashish Tawari, Sayanan Sivaraman, Mohan M. Trivedi, Trevor Shannon and Mario Tippelhofer, "Looking-in and Looking-out Vision for Urban Intelligent Assistance: Estimation of driver Attentive State and Dynamic Surround for Safe Merging and Braking", IEEE Intelligent Vehicles Sym, June 2014.

  • Ashish Tawari, Sujitha Martin and Mohan M. Trivedi, "Continuous Head Movement Estimator (CoHMET) for Driver Assistance: Issues, Algorithms and On-Road Evaluations," IEEE Transactions on Intelligent Transportation Systems, 2014.

  • Sujitha Martin, Ashish Tawari and Mohan M. Trivedi, "Towards Privacy Protecting Safety Systems for Naturalistic Driving Videos," IEEE Transactions on Intelligent Transportation Systems, 2014.

  • Eshed Ohn-Bar, Ashish Tawari, Sujitha Martin, and Mohan M. Trivedi, "Surveillance for Safety Critical Events: In-Vehicle Video Networks for Predictive Driver Assistance Systems," accepted and to appear in Computer Vision and Image Understanding (CVIU), 2014.

  • Ashish Tawari and Mohan M. Trivedi, "Face Expression Recognition by Cross Modal Data Association," IEEE Transactions on Multimedia, vol.15, no.7, pp. 1543-1552, Nov. 2013.

  • Ashish Tawari and Mohan M. Trivedi, “Head Dynamic Analysis: A Multi-view Framework,” New Trends in Image Analysis and Processing, IEEE Int. Conf. on Image Analysis and Processing , September 2013.

  • Ashish Tawari and Mohan M. Trivedi, "Audio-Visual Data Association for Face Expression Analysis," 21st IEEE International Conference on Pattern Recognition (ICPR), November, 2012. [oral presentation]

  • Toshiro Yamada, Ashish Tawari and Mohan M. Trivedi, "In-Vehicle Speaker Recognition Using Independent Vector Analysis," 15th IEEE Intelligent Transportation Systems Conference, (ITSC), September, 2012.

  • Ashish Tawari and Mohan M. Trivedi"Audio Visual Cues in Driver Affective State Characterization: Issues and Challenges in Developing Robust Approaches", IEEE Int. Joint Conf. on Neural Networks, July 2011. [oral presentation]

  • Ashish Tawari and Mohan M. Trivedi, "Speech Emotion Analysis in Noisy Real-World Environment," 20th International Conference on Pattern Recognition (ICPR), 2010.

  • Ashish Tawari and Mohan M. Trivedi, "Speech Emotion Analysis: Exploring the Role of Context," IEEE Transactions on Multimedia, vol.12, no.6, pp. 502-509, Oct. 2010.

Awards:

  • Awarded Certificate of Appreciation for Outstanding contributions to UC San Diego community, 2013.

  • Awarded QUALSTAR, a reward program for exceptional contribution, for improving the lower band MDCT encoding performance in the design of 4th generation vocoder to handle music signal over voice channel (Sept 2010).

  • Honorable Mention, 2010 IEEE Intelligent Vehicles Symposium Ph.D. Forum (Jun 2010).

  • Recipient of Powell fellowship 2008-2011 at UCSD.

  • Awarded QUALSTAR for designing and implementing MALLOC feature (April 2008).

  • Awarded QUALSTAR for providing innovative ideas and technical assistance in development of the Low Power MP3 experiment (Aug 2007).

  • Awarded QUALSTAR, for contribution in evaluating Sony VME technology for audio subsystem (Dec 2007).

  • Recipient of Hostel Organizational Color, 2004.

  • Recipient of Certificate of Excellence from EESA for poster presentation in "Image processing" (2003).

  • Recipient of Hostel Sports Color, 2002-03.

  • Accomplished a position in top 0.1% out of 125,000 candidates in IIT JEE 2002.

Extracurricular Activities:

  • Organizing Committee, IEEE Intelligent Vehicles Symposium, June 2010.

  • Secured 1st position in inter hostel football match, 2004.

  • Held the post of Sports Secretary of hostel 5, 2003-04.

  • Organizer in workshops, Techfest, annual technology festival of IITB, 2003.

  • Lead the hostel Kho-Kho team as captain, 2003.

  • Held the post of Head Boy of the school, 2000-01.